Use current workflow steps to control medical data processing

Abstract

A computer-implemented method for adapting a biomechanical model of an anatomical body part of a patient to a current state of the patient is disclosed. The method comprises determining a currently performed workflow step, such as a medical intervention, and the result of the determination is used as a basis for adapting and / or updating the biomechanical model of the anatomical body part to the corresponding current state of the patient. Determining the current workflow step may also be used as a basis for controlling an imaging device for tracking entities surrounding the patient; or for imaging the anatomical body part; or for acquiring further data; or for prompting a user to perform a specific action, such as acquiring information using a tracking instrument, such as a pointer. The biomechanical model is generated based on atlas data. The data set generated based on the current workflow step may additionally or alternatively be used as a basis for determining the current workflow step and / or for adapting further workflows.

Description

Technical Field

[0001] The invention relates to a computer-implemented method for adapting a biomechanical model of an anatomical body part of a patient to the current state of the patient, a corresponding computer program, a computer-readable storage medium storing such a program and a computer executing the program, as well as a medical system comprising an electronic data storage device and such a computer. Background Art

[0002] Biomechanical models are used, for example, to describe anatomical changes that may be caused by a medical intervention and, accordingly, to update patient image data used to plan and guide the intervention. It is also known to base such updates on spatially sampled data generated during the intervention, such as medical image data.

[0003] It is an object of the present invention to improve the use of digital biomechanical models of anatomical body parts.

[0004] The present invention can be used, for example, in processes relating to medical guidance systems and image registration software, respectively, both products of Brainlab AG, such as Cranial Navigation and Image Fusion.

[0005] US 2018 / 0078313 A1 discloses the use of multiple imaging modalities to model the liver based on medical scan data. Multiple imaging modalities are used for liver modeling based on medical scan data. By combining multiple imaging modalities with generative modeling, a more comprehensive and informed assessment can be made. Derivative modeling can provide feedback on the impact of proposed treatments on liver function. This feedback is used to update liver function information based on imaging. Computerized modeling based on information from various imaging modalities can provide output based on more comprehensive information and patient-specific modeling and feedback to assist physicians.

[0006] US 2016 / 0005169 A1 discloses a method for generating an evolvable tissue model of a patient, and using the model, modeling physical transformations (e.g., deformations) of the tissue model by causing the tissue model to interact with an influence model, wherein the influence model models interactions with the tissue (e.g., surgical instruments, pressure, swelling, temperature changes, etc.). The model is generated by a set of tissue input data that includes tissue directional information. The directional information is used to generate a directional tissue map. A tissue model is then generated based on the directional tissue map so that the tissue model reflects the directionality of the tissue components. When the tissue model is subjected to an influence that causes the tissue to deform over a period of time, the tissue model deforms directionally over this period of time in a manner that reflects the trajectory of the influence that interacts with the directional nature of the tissue components.

[0007] The following discloses various aspects, examples and exemplary steps of the present invention and its embodiments. The different exemplary features of the present invention can be combined according to the invention whenever this is technically advantageous and feasible. Summary of the Invention

[0008] Brief Description of Exemplary Inventions

[0009] In the following, a brief description of specific features of the present invention is given, which should not be understood as limiting the present invention to only the features or feature combinations described in this section.

[0010] The method of the present disclosure comprises determining a currently performed workflow step, such as a medical intervention, and the result of the determination is used as a basis for adapting and / or updating a biomechanical model of an anatomical body part to a current state corresponding to the patient. Determining the current workflow step may also be used as a basis for controlling an imaging device for tracking entities surrounding the patient, or for imaging the anatomical body part or for acquiring further data, or for prompting a user to perform a specific action, such as acquiring information using a tracking instrument such as a pointer. The biomechanical model is generated based on atlas data. The data set generated based on the current workflow step may additionally or alternatively be used as a basis for determining the current workflow step and / or for adapting further workflows. SUMMARY OF THE INVENTION

[0012] In this section, a description of general features of the invention is given, for example, by reference to possible embodiments of the invention.

[0013] In general, the present invention achieves the above-mentioned objectives by, in a first aspect, providing a computer-implemented method for adapting a biomechanical model of a patient's anatomical body part to the patient's current condition. The method comprises executing the following exemplary steps on at least one processor of at least one computer (e.g., at least one computer being part of a guidance system) and performed by the at least one processor.

[0014] In an exemplary (e.g., first) step, initial biomechanical model data is acquired, the initial biomechanical model data describing an initial biomechanical model of an anatomical body part. For example, the biomechanical model is a finite element model or a coupled spring model of the anatomical body part. For example, the initial biomechanical model data is generated based on atlas-based segmentation of patient image data describing a digital medical image of the anatomical body part, i.e., by mapping between atlas data (which describes the image-based model of the anatomical body part) and patient image data (which describes the digital medical image of the anatomical body part) to segment an image representation of the anatomical body part. For example, the anatomical body part includes at least a portion of the brain or at least a portion of the liver.

[0015] In an exemplary (e.g., second) step, workflow step data is acquired, the workflow step data describing a current workflow step of a procedure to be performed on a patient. For example, tracking data describing a location of a medical entity (i.e., at least one of a patient, a medical practitioner, or a medical instrument) is acquired; and workflow step definition data describing an association between at least one location of the medical entity (i.e., at least one of the patient, the medical practitioner, or the medical instrument) and at least one workflow step of the procedure to be performed on the patient is acquired. For example, based on the tracking data and the workflow step definition, the workflow step data is then acquired by comparing the location described by the tracking data with the workflow step definition data, and selecting at least one workflow step associated with the location of the medical entity corresponding to the location of the medical entity described by the tracking data as the current workflow step. For example, the tracking data is generated by imaging (e.g., video imaging) at least one medical entity (e.g., at least one of a patient, an anatomical body part, a medical practitioner, or a medical instrument). According to another example, the tracking data is generated by optically or electromagnetically tracking at least one marker device attached to at least one medical entity (e.g., at least one of the patient, the anatomical body part, the medical practitioner, or the medical instrument).

[0016] In an exemplary (e.g., third) step, state change data is determined based on the workflow step data and the initial biomechanical model data, wherein the state change data describes a patient state change. For example, the patient state change is a change in at least one of: a position or geometry of the patient's body, such as the position or geometry of an anatomical body part; or a relative position between a medical instrument and the patient's body, or a relative position between a medical person and the patient's body; a time interval between changes in at least one of the above positions; a configuration or use of a medical instrument; a time interval for a medical instrument to reach a specific position, or a time interval that has elapsed since a predetermined point in a procedure.

[0017] In an exemplary (e.g., fourth) step, model adaptability data is obtained that describes the correlation between changes in the patient's state and adaptability to be applied to the initial biomechanical model. The adaptability is defined, for example, as changes in boundary conditions of a finite element model or a coupled spring model, such as by moving nodes, changing, adding, or removing mass points, or changing, adding, or removing forces, respectively.

[0018] In an exemplary (e.g., fifth) step, adaptive biomechanical model data is determined based on the initial biomechanical model data, the state change data, and the model adaptability data, wherein the adaptive biomechanical model data describes an adaptive biomechanical model determined by applying adaptivity to the initial biomechanical model. For example, the adaptive biomechanical model is determined by changing boundary conditions of a finite element model or a coupled spring model, such as by adding, deleting, or moving nodes, changing, adding, or deleting mass points, or changing, adding, or deleting forces, respectively.

[0019] In an example of the method according to the first aspect, region of interest (ROI) data is acquired based on state change data, wherein the region of interest describes an area or trajectory within or on a process to be performed (e.g., the process described above), such as an anatomical region or an object surface. For example, the method according to the first aspect includes acquiring instrument position data based on the region of interest data, the instrument position data describing the position of a guiding instrument. The guiding instrument is, for example, a pointing device for identifying a position (e.g., a position on an anatomical body part), such as a pointer (e.g., a contactless pointer, such as a laser pointer, or a pointer for identifying the position by placing its tip on the position). For example, the instrument position data is used as an additional basis for determining adaptive biomechanical model data. Therefore, the guiding instrument can be used as an input device for inputting position information into a position tracking system, which is used to track the position of the guiding instrument and identify the position on the anatomical body part. For example, the position on the anatomical body part can be identified by determining the position of the pointing device when it is pointed at the anatomical body part. For example, at least one position described by the instrument position data is used to change the boundary conditions of the finite element model or the coupled spring model, such as to identify or add or delete a node of the initial biomechanical model, move the node, change or add or delete a mass point, or change or add or delete a force. Alternatively or additionally, the process includes acquiring video or medical image data describing at least a portion of the patient (e.g., an anatomical body part) based on the region of interest data. For example, the process includes acquiring medical image data, and the imaging device for generating the medical image data is handheld or manually guided or head-mounted or automatically guided, for example, by a robotic arm. In a further example, the imaging device is a handheld or manually guided or head-mounted or fixed ultrasound probe, or a handheld or manually guided or head-mounted or fixed infrared camera, or a three-dimensional image generating scanner, such as a scanner for computed tomography or magnetic resonance tomography. For example, medical image data is used as a basis for determining adaptive biomechanical data, such as by using image information contained in the medical image data to change boundary conditions of a finite element model or a coupled spring model to, for example, identify or add or delete a node of an initial biomechanical model, move such a node, change or add or delete a mass point, or change or add or delete a force.

[0020] In an example of the method according to the first aspect, imaging control data is determined based on the state change data. The imaging control data describes a command to be issued to a medical imaging device to capture an image of at least a portion of an anatomical body part. For example, the portion of the anatomical body part to be imaged depends on the type of state change of the patient. For example, the portion of the anatomical body part to be imaged anatomically corresponds to a portion of the biomechanical model adapted to determine the adaptive biomechanical model data. For example, the imaging control data is transmitted to the medical imaging device and executed to determine medical image data describing a medical image of the portion of the anatomical body part to be imaged.

[0021] In an example of the method according to the first aspect, instrument guidance data is determined based on the state change data. The instrument guidance data describes the position of the instrument to be positioned. For example, the instrument is a guiding instrument, such as a pointing device, such as a pointer. Therefore, information on where to position the instrument (for example, visual guidance information for guiding the user or control information for controlling the robotic device) can be provided to a user or a robotic device for moving such an instrument, for example, to change the boundary conditions of a finite element model or a coupled spring model, for example, to identify or add or delete a node of an initial biomechanical model, to move this node, to change or add or delete a mass point, or to change or add or delete a force.

[0022] In an example of the method according to the first aspect, imaging device guidance data is determined based on the state change data, wherein the imaging device guidance data describes a position where the medical imaging device is to be positioned, for example, to enable the capture of images of an anatomical body part. Thus, information on where to position the instrument (e.g., visual guidance information for guiding the user or control information for controlling the robotic device) can be provided to a user or a robotic device for moving the imaging device.

[0023] In a second aspect, the present invention relates to a computer program comprising instructions that, when executed by at least one computer, cause the at least one computer to perform a method according to the first aspect. Alternatively or additionally, the present invention may relate to a signal wave (e.g., physically, e.g., electronically, generated by technical means) carrying information representing a program (e.g., the program described above), such as a digital signal wave, such as an electromagnetic carrier wave. The program described above, for example, comprises code means suitable for performing any or all of the steps of the method according to the first aspect. In one example, the signal wave is a data carrier signal carrying the computer program described above. The computer program stored on a disk is a data file; when the file is read and transmitted, the file becomes a data stream, such as in the form of a signal (e.g., physically, e.g., electronically, generated by technical means). The signal may be implemented as a signal wave, such as the electromagnetic carrier wave described herein. For example, the signal (e.g., signal wave) is configured to be transmitted via a computer network, such as a LAN, WLAN, WAN, or a mobile network (e.g., the Internet). For example, the signal (e.g., signal wave) is configured to be transmitted via optical or acoustic data transmission. Therefore, alternatively or additionally, the present invention according to the second aspect may relate to a data stream representing the program described above (i.e., including the program).

[0024] In a third aspect, the present invention relates to a computer-readable storage medium having stored thereon the program according to the second aspect. The program storage medium is, for example, non-transitory.

[0025] In a fourth aspect, the invention relates to at least one computer (e.g. a computer) comprising at least one processor (e.g. a processor), wherein the program according to the second aspect is executed by the processor, or wherein the at least one computer comprises a computer-readable storage medium according to the third aspect.

[0026] In a fifth aspect, the present invention relates to a medical system comprising:

[0027] a) at least one computer according to the fourth aspect;

[0028] b) at least one electronic data storage device storing at least initial biomechanical model data and model adaptation data; and

[0029] c) Medical devices used to perform medical procedures on patients.

[0030] The at least one computer is operatively coupled to at least one electronic data storage device for retrieving at least the initial biomechanical model data and the model adaptation data from the at least one data storage device and for storing the adapted biomechanical model data in the at least one data storage device.

[0031] In a sixth aspect, the present invention relates to the use of a system according to the preceding claims for performing a medical procedure, wherein the use comprises performing the steps of a method according to any of the preceding claims to adapt a biomechanical model of an anatomical body part of a patient to the current patient state.

[0032] For example, the present invention does not involve or particularly does not include or encompass invasive procedures that represent substantial physical intervention with the body requiring specialized medical care and measures that may expose the body to significant health risks even with the required specialized care and measures.

[0033] definition

[0034] In this section, definitions of specific terms used in this disclosure are provided, which also constitute a part of this disclosure.

[0035] The method according to the present invention is, for example, a computer-implemented method. For example, all or only some (i.e., less than the total number of) steps of the method according to the present invention can be performed by a computer (e.g., at least one computer). One embodiment of a computer-implemented method is a method that uses a computer to perform a data processing method. One embodiment of a computer-implemented method is a method that involves the operation of a computer, such that the computer is operated to perform one, more, or all of the steps of the method.

[0036] A computer, for example, comprises at least one processor and at least one memory for (technically) processing data, for example, electronically and / or optically. The processor, for example, is made of a semiconductor substance or composition, for example, at least partially n-type and / or p-type doped semiconductors, for example, at least one of type II, III, IV, V, or VI semiconductor materials, for example, (doped) silicon and / or gallium arsenide. The described calculation steps or determination steps are, for example, performed by a computer. A determination step or calculation step is, for example, a step of determining data within the framework of a technical method (for example, within the framework of a program). A computer is, for example, any type of data processing device, for example, an electronic data processing device. A computer can be a device generally considered to be of this type, such as a desktop personal computer, a laptop, a netbook, etc., or any programmable device, such as a mobile phone or an embedded processor. A computer can, for example, comprise a system (network) with "sub-computers," each of which represents its own computer. The term "computer" includes cloud computers, such as cloud servers. The term "computer" includes server resources. The term "cloud computer" includes cloud computer systems, which include, for example, a system having at least one cloud computer (e.g., a plurality of operably interconnected cloud computers, such as a server farm). Such cloud computers are preferably connected to a wide area network, such as the World Wide Web (WWW), and are located in a so-called cloud of computers that are all connected to the World Wide Web. This infrastructure is used for "cloud computing," which describes those computing, software, data access, and storage services that do not require the end user to know the physical location and / or configuration of the computer providing the particular service. For example, the term "cloud" is used metaphorically to refer to the Internet (World Wide Web). For example, the cloud provides computing infrastructure as a service (IaaS). Cloud computers can be used as virtual hosts for operating systems and / or data processing applications for executing the method of the present invention. Cloud computers are, for example, hosted by Amazon Web Services. TM)TM provided by Elastic Compute Cloud (EC2). The computer, for example, includes an interface for receiving or outputting data and / or performing analog-to-digital conversion. The data is, for example, data representing physical properties and / or generated by technical signals. The technical signals are, for example, generated by a (technical) detection device (e.g., a device for detecting a marking device) and / or a (technical) analysis device (e.g., a device for performing a (medical) imaging method), wherein the technical signals are, for example, electrical signals or optical signals. The technical signals represent, for example, data received or output by the computer. The computer is preferably operably coupled to a display device that allows information output by the computer to be displayed to, for example, a user. An example of a display device is a virtual reality device or an augmented reality device (also known as virtual reality glasses or augmented reality glasses), which can be used as "goggles" for guidance. A specific example of such augmented reality glasses is Google Glass (a trademark brand of Google, Inc.). The augmented reality device or virtual reality device can be used both to input information into the computer through user interaction and to display information output by the computer. Another example of a display device is a standard computer monitor, for example including a liquid crystal display screen, operatively coupled to a computer for receiving display control data from a computer generating a signal to display image information content on the display device. A specific embodiment of such a computer monitor is a digital light box. An example of such a digital light box is It is a product of Brainlab AG. The monitor can also be a monitor of a handheld portable device, such as a smartphone or a personal digital assistant or a digital media player, for example.

[0037] The present invention also relates to a computer program comprising instructions that, when executed by a computer, cause the computer to perform one or more of the methods described herein, such as steps of one or more of the methods; and / or to a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium) storing the program; and / or to a computer comprising the program storage medium; and / or to a signal wave (e.g., a physical, e.g., electrical, signal wave generated by technical means), such as a digital signal wave, such as an electromagnetic carrier wave, carrying information representing a program (e.g., the program described above), the program comprising, for example, code means suitable for performing any or all of the steps of the method described herein. In one example, the signal wave is a data carrier signal carrying the computer program described above. The present invention also relates to a computer comprising at least one processor and / or the computer-readable storage medium described above and, for example, a memory, wherein the program is executed by a processor.

[0038] Within the framework of the present invention, computer program elements may be embodied in hardware and / or software (this includes firmware, resident software, microcode, etc.). Within the framework of the present invention, computer program elements may take the form of a computer program product, which may be embodied in a computer-usable, e.g., computer-readable, data storage medium comprising computer-usable, e.g., computer-readable program instructions, the "code" or "computer program" embodied in the data storage medium being intended for use on or in conjunction with an instruction execution system. Such a system may be a computer; a computer may be a data processing device comprising means for executing a computer program element and / or program according to the present invention, e.g., a data processing device comprising a digital processor (central processing unit or CPU) that executes a computer program element, and optionally comprising volatile memory (e.g., random access memory or RAM) for storing data used for and / or generated by executing the computer program element. Within the framework of the present invention, a computer-usable, e.g., computer-readable data storage medium may be any data storage medium that can contain, store, communicate, propagate, or transmit programs for use on or in conjunction with an instruction execution system, apparatus, or device. Computer-usable, e.g., computer-readable, data storage media can be, for example, but not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or apparatuses, or communication media such as the Internet. A computer-usable or computer-readable data storage medium can even be, for example, paper or other suitable media on which a program can be printed, since the program can be obtained electronically, e.g., by optically scanning the paper or other suitable media, and then compiled, interpreted, or otherwise processed in an appropriate manner. The data storage medium is preferably a non-volatile data storage medium. The computer program product and any software and / or hardware described herein form various means for performing the functions of the present invention in the exemplary embodiments. The computer and / or data processing device can, for example, include a guidance information device that includes means for outputting guidance information. The guidance information can be output to the user, for example, visually via visual indication means (e.g., a monitor and / or light) and / or audibly via auditory indication means (e.g., a speaker and / or digital voice output device) and / or tactilely via tactile indication means (e.g., a vibration element or a vibration element incorporated into the instrument). For the purposes of this document, a computer is a technical computer, eg comprising technical components such as tangible components, eg mechanical components and / or electronic components, etc. Any device mentioned as such in this document is a technical device and is eg a tangible device.

[0039] The term "acquiring data" includes, for example, scenarios where data is determined by a computer-implemented method or program (within the framework of a computer-implemented method). Determining data includes, for example, measuring a physical quantity and converting the measured value into data, such as digital data, and / or calculating (e.g., outputting) the data with the aid of a computer, such as within the framework of the method according to the present invention. A "determining" step as described herein may, for example, include or consist of issuing a command to perform a determination as described herein. For example, this step may include or consist of issuing a command to cause a computer (e.g., a remote computer, such as a remote server, such as in the cloud) to perform the determination. Alternatively or additionally, a "determining" step as described herein may include or consist of receiving result data from a determination as described herein, such as from a remote computer (e.g., from the remote computer that performed the determination). "Acquiring data" also includes, for example, scenarios where data is received or retrieved by (e.g., input into) a computer-implemented method or program, such as from another program, a previous method step, or a data storage medium, such as for further processing by the computer-implemented method or program. Generating the data to be acquired may, but need not, be part of the method according to the present invention. Therefore, the expression "obtaining data" can also, for example, represent waiting to receive data and / or receiving data. The received data can, for example, be input via an interface. The expression "obtaining data" can also represent a computer-implemented method or program execution step so that (actively) from a data source such as a data storage medium (such as ROM, RAM, database, hard drive, etc.) or via an interface (such as from another computer or network) to receive or retrieve data. The data obtained by the method or device of the present invention can be obtained from a database located in a data storage device, which is operably connected to a computer so that data can be transferred between the database and the computer, such as from a database to the computer. The computer obtains data to be used as the input of the "determining data" step. The determined data can be output to the same or another database again so that it can be stored for subsequent use. The database or the database for implementing the disclosed method can be located in a network data storage device or a network server (such as a cloud data storage device or a cloud server) or a local data storage device (such as a large-capacity storage device operably connected to at least one computer that performs the disclosed method). The data can be "ready" by performing an additional step before the acquisition step. According to the additional step, data is generated for acquisition. The data are for example detected or acquired (for example by an analysis device). Alternatively or additionally, the data are input according to an additional step (for example via an interface). For example, the generated data can be input (for example, into a computer).According to an additional step (which is performed before the acquisition step), the data can also be provided by performing an additional step of storing the data on a data storage medium (such as a ROM, RAM, CD and / or hard drive), thereby making the data ready within the framework of the method or program according to the present invention. Therefore, the step of "acquiring data" can also involve instructing the device to acquire and / or provide the data to be acquired. In particular, the acquisition step does not involve an invasive step representing a substantial physical intervention on the body, which would require professional medical measures to be taken on the body, and even if the required professional care and measures are taken, the body may still be exposed to significant health risks. In particular, the step of acquiring data (e.g., determining data) does not involve a surgical step, in particular, does not involve a step of treating the human or animal body using surgery or therapy. In order to distinguish the different data used in the present method, the data are denoted (i.e., referred to) as "XY data" or the like, and are defined according to the information they describe, and are then preferably referred to as "XY information" or the like.

[0040] Preferably, atlas data is acquired that describes (e.g. defines, more particularly represents and / or serves as) the general three-dimensional shape of an anatomical body part. Thus, the atlas data represents an atlas of an anatomical body part. An atlas typically consists of a plurality of object generic models, wherein these object generic models together form a composite structure. For example, an atlas constitutes a statistical model of a patient's body (e.g. a part of a body), which statistical model has been generated based on anatomical information collected from a plurality of human bodies, e.g. based on medical image data comprising images of these human bodies. Thus, in principle, the atlas data represents the result of a statistical analysis of such medical image data of a plurality of human bodies. This result can be output as an image - the atlas data thus contains or is equivalent to the medical image data. Such a comparison can be performed, for example, by applying an image fusion algorithm, wherein the image fusion algorithm performs image fusion between the atlas data and the medical image data. The comparison result can be a similarity measure between the atlas data and the medical image data. The atlas data includes image information (e.g., position image information) that can be matched (e.g., by applying an elastic or rigid image fusion algorithm) with image information (e.g., position image information) contained in, for example, medical image data, so as to, for example, compare the atlas data with the medical image data to determine the locations of anatomical structures in the medical image data that correspond to anatomical structures defined by the atlas data.

[0041] The human body (whose anatomical structure is used as input for generating the atlas data) advantageously shares common characteristics, such as gender, age, race, body measurements (e.g., height and / or weight), and at least one of a pathological state. The anatomical information, for example, describes the human anatomical structure and is extracted, for example, from medical image information about the human body. For example, an atlas of the femur may include the femoral head, femoral neck, body, greater trochanter, lesser trochanter, and lower limb as objects that together constitute a complete structure. For example, an atlas of the brain may include the telencephalon, cerebellum, diencephalon, pons, midbrain, and medulla oblongata as objects that together constitute a complex structure. One application of such an atlas is in medical image segmentation, where an atlas is matched to medical image data and the image data is compared to the matched atlas so as to assign points (pixels or voxels) of the image data to objects of the matched atlas, thereby segmenting the image data into objects.

[0042] For example, the atlas data includes information about an anatomical body part. The information is, for example, at least one of patient-specific, non-patient-specific, indication-specific, or non-indication-specific. Thus, the atlas data describes, for example, at least one of a patient-specific, non-patient-specific, indication-specific, or non-indication-specific atlas. For example, the atlas data includes movement information indicating the degrees of freedom of movement of an anatomical body part relative to a given reference (e.g., another anatomical body part). For example, the atlas is a multimodal atlas that defines atlas information for a plurality of (i.e., at least two) imaging modes and includes mappings between atlas information in different imaging modes (e.g., mappings between all modes) such that the atlases can be used to transform medical image information from its image depiction in a first imaging mode to its image depiction in a second imaging mode different from the first imaging mode, or to compare different imaging modes with each other (e.g., to match or register).

[0043] In the medical field, imaging methods (also referred to as imaging modalities and / or medical imaging modalities) are used to generate image data (e.g., two-dimensional or three-dimensional image data) of human anatomical structures (e.g., soft tissue, bones, organs, etc.). The term "medical imaging method" should be understood to mean (advantageously device-based) imaging methods (e.g., so-called medical imaging modalities and / or radiological imaging methods), such as computed tomography (CT) and cone-beam computed tomography (CBCT, such as volumetric CBCT), x-ray tomography, magnetic resonance tomography (MRT or MRI), conventional x-rays, ultrasound scanning and / or ultrasonography, and positron emission tomography. For example, the medical imaging method is performed by an analysis device. Examples of medical imaging modalities used by medical imaging methods are: x-rays, magnetic resonance imaging, medical ultrasound scanning or ultrasound, endoscopy, elastography, tactile imaging, thermography, medical photography, and nuclear medicine functional imaging techniques such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT). The image data generated thereby is also referred to as "medical imaging data." The analysis device is used, for example, to generate image data in an apparatus-based imaging method. Imaging methods are used, for example, for medical diagnosis of anatomical body structures to generate images described by image data. Imaging methods are also used, for example, to detect pathological changes in the human body. However, some changes in the anatomical structure, such as pathological changes in the structure (tissue), may not be detected and, for example, such changes may not be visible in an image generated by the imaging method. A tumor represents an example of a change in an anatomical structure. If a tumor grows, it can be considered to represent an expanded anatomical structure. This expanded anatomical structure may not be detected, for example, only a portion of the expanded anatomical structure may be detectable. For example, early / late stage brain tumors are often visible in MRI scans when a contrast agent is used to infiltrate the tumor. MRI scans represent an example of an imaging method. When an MRI scan is performed on such a brain tumor, the signal enhancement in the MRI image (caused by the contrast agent infiltrating the tumor) is considered to represent a solid tumor mass. Therefore, the tumor can be detected and, for example, can be distinguished in an image generated by the imaging method. In addition to these tumors, known as "enhancing" tumors, approximately 10% of brain tumors are believed to be indistinguishable on scans and are not visible, for example, to a user viewing an image generated by the imaging method.

[0044] The mapping describes a transformation (e.g., a linear transformation) of elements (e.g., pixels or voxels, e.g., element positions) of a first dataset in a first coordinate system into elements (e.g., pixels or voxels, e.g., element positions) of a second dataset in a second coordinate system (e.g., a basis of the second coordinate system that is different from the basis of the first coordinate system). In one embodiment, the mapping is determined by comparing (e.g., matching) the color values (e.g., grayscale values) of each element using an elastic or rigid fusion algorithm. The mapping is embodied, for example, by a transformation matrix (e.g., a matrix defining an affine transformation).

[0045] The pointer is, for example, a rod comprising one or more, advantageously two, markers fixed to the rod and which can be used to measure a single coordinate on a part of the body, for example a spatial coordinate (i.e. a three-dimensional coordinate), wherein the user guides the pointer (e.g. a part of the pointer having a defined and advantageously fixed position relative to at least one marker attached to the pointer) to a position corresponding to the coordinate, so that the position of the pointer can be determined by using a guidance system (also called a position tracking system) to, for example, optically or electromagnetically detect the markers on the pointer. For example, the relative position between the markers of the pointer and the part of the pointer used to measure the coordinate (e.g. the tip of the pointer) is known. The surgical guidance system is then able to assign the position (of the three-dimensional coordinate) to a predetermined body structure, wherein the assignment can be performed automatically or through user intervention. In another example, the pointer is a light pointer (e.g. a laser pointer) which identifies a position by irradiating it with a narrow light beam. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Hereinafter, the present invention will be described with reference to the accompanying drawings, which provide a background to the present invention and show specific embodiments of the present invention. However, the scope of the present invention is not limited to the specific features disclosed in the context of the accompanying drawings, in which:

[0047] Figure 1 illustrates a basic flow chart of the method according to the first aspect;

[0048] Figure 2 The application of the method according to the first aspect is shown; and

[0049] Figure 3 is a schematic diagram of a system according to the fifth aspect. DETAILED DESCRIPTION

[0050] Figure 1 The basic steps of the method according to the first aspect are described, wherein step S1 comprises obtaining initial biomechanical model data, step S2 comprises obtaining workflow step data, and then step S3 comprises determining state change data. The method then continues with obtaining model adaptability data in step S4 and determining adaptive biomechanical model data in step S5.

[0051] Figure 2An application of the method according to the first aspect is described. Workflow data 4 is acquired and current workflow data is determined for corresponding adaptation of a biomechanical model 10. The workflow data 4 can also serve as the basis for triggering 7 the input of other intra-procedural data 8 or using 9 other intra-procedural data 8 to adapt a biomechanical model 10, which was initially generated by generating 11 a model based on atlas data 12. The adaptive biomechanical model 10 can also be used to feed back into the workflow to determine the current workflow step based on the adaptive biomechanical model 10, for example, to determine whether workflow step data should be replaced with the latest image data as the basis for adapting the biomechanical model 10. The current workflow step can be determined 6 based on image data as video data 1, using a tracking imaging device 2 (e.g., a microscope), or based on the intra-procedural data 8. The image data can also be used to directly adapt the biomechanical model 10. The current workflow step can also be used to initiate imaging, for example, using a tomography scanner 5, where the generated image can be used as the basis for adapting the biomechanical model 10. The current workflow step can also be used as the basis for initiating the acquisition of position data using a tracking instrument 3. Image data generated using the tomography scanner 5 can also be used to determine the current workflow step. The current workflow step may also be used to initiate the operation of a video camera or tracking imaging device 2 for generating image data 1. The use of a tracking pointer 3 may also be used as a basis for determining the current workflow step.

[0052] Figure 3 1 is a schematic diagram of a medical system 13 according to the fifth aspect. The system is generally designated by reference numeral 13 and includes a computer 14 and an electronic data storage device (e.g., a hard disk) 15 for storing at least patient data. The components of the medical system 13 have the functions and characteristics described above in relation to the fifth aspect of the present disclosure.

[0053] The following exemplary aspects are also part of possible embodiments of the present invention.

[0054] - Initial biomechanical model data is generated based on the physical (eg mechanical) properties of tissue types (eg tissue classes) stored in the atlas.

[0055] - Workflow step data can be generated based on: intraoperative image data (e.g., from an x-ray device, fluoroscopy device, x-ray tomography scanner, magnetic resonance tomography scanner, C-arm), intraoperative video data (e.g., from an endoscope, microscope, exoscope, or external camera viewing the surgical site), ultrasound image data, position, velocity, and acceleration (e.g., as a function of time) of an instrument or imaging device. Workflow step data can be based on content of the intraoperative video data, such as the position or velocity or acceleration (e.g., as a function of time) of an instrument or implant or anatomical object in the image.

[0056] - The workflow step data may also be based on other intraoperative or in-procedure data, such as the status of a device in the operating room, eg "open" or "closed", which may be, for example, an anesthesia device. Patient physiological data.

[0057] - Workflow step data may be determined by comparing the intraoperative data to predetermined criteria (such as predetermined patterns of other intraoperative image data, video data or other intraoperative data) using predetermined relationships between patterns and workflow steps.

[0058] Workflow step data can also be determined using a learning algorithm. During the learning phase, events are manually labeled and fed into the learning algorithm along with intraoperative data. The learning algorithm can be based on, for example, a convolutional neural network or a recurrent neural network. Following the learning phase, in the learning algorithm's use phase, intraoperative data is fed in, and events are output by the learning algorithm based on the learning data acquired during the learning phase.

[0059] The workflow step data may also be based on a stored workflow for the type of process being performed. Such stored workflows may comprise a number of predefined steps.

[0060] - Current workflow steps are, for example, opening the dura, performing a resection, performing a craniotomy, installing a drain, positioning the patient, applying suction, aspirating CSF, removing tissue, administering medication.

[0061] - Status change data includes, for example, that the dura has been opened, the resection has been performed, and the instrument is in place.

[0062] - A handheld or manually guided or automatically guided imaging device such as an ultrasound probe, a microscope or an endoscope.

[0063] - To support image acquisition by a handheld device, the ROI may be indicated to the user on a display (eg an augmented reality display).

Claims

1. A computer-implemented method of adapting a biomechanical model of an anatomical body part of a patient to a current condition of the patient, the method comprising: a) acquiring initial biomechanical model data, wherein the initial biomechanical model data describes an initial biomechanical model of the anatomical body part; b) obtaining workflow step data describing a current workflow step of a procedure to be performed on the patient; c) determining state change data based on the workflow step data and the initial biomechanical model data, wherein the state change data describes a state change of the patient; d) acquiring model adaptability data, the model adaptability data describing a correlation between the change in the patient's state and adaptability to be applied to the initial biomechanical model; e) determining adaptive biomechanical model data based on the initial biomechanical model data, the state change data and the model adaptability data, wherein the adaptive biomechanical model data describes an adaptive biomechanical model determined by applying the adaptability to the initial biomechanical model, Wherein, imaging device guidance data is determined based on the state change data, wherein the imaging device guidance data describes a position where the medical imaging device is to be positioned.

2. The method according to claim 1, comprising: Region of interest data is acquired based on the state change data, wherein the region of interest describes a region for which a process is to be performed.

3. The method according to claim 2, comprising: Acquire instrument position data based on the region of interest data, the instrument position data describing the position of the guidance instrument, and / or Medical image data is acquired based on the region of interest data, the medical image data describing at least a portion of an anatomical body part of the patient.

4. The method according to claim 3, comprising: Acquire the medical image data, wherein the medical imaging device used to generate the medical image data is handheld or manually guided or head mounted or automatically guided, including an ultrasonic imaging probe, a three-dimensional image generating scanner, or a handheld or manually guided or head mounted or fixed infrared camera.

5. The method according to claim 3, comprising: acquiring the instrument position data, wherein the adaptive biomechanical model data is determined based on the instrument position data, and / or The medical image data is acquired, wherein the adaptive biomechanical model data is determined based on the medical image data.

6. The method according to claim 1, comprising: Imaging control data is determined based on the state change data, wherein the imaging control data describes a command to be issued to a medical imaging device to capture an image of at least a portion of the anatomical body part.

7. The method according to claim 6, wherein: The portion of the anatomical body part to be imaged depends on the type of change in the patient's condition.

8. The method according to claim 7, wherein: The portion of the anatomical body part to be imaged corresponds anatomically to the portion of the biomechanical model adapted for determining the adaptive biomechanical model data.

9. The method according to claim 8, wherein The imaging control data is transmitted to the medical imaging apparatus and executed in order to determine medical image data describing a medical image of the portion of the anatomical body part to be imaged.

10. The method according to claim 1, wherein The biomechanical model is a finite element model or a coupled spring model of the anatomical body part, and wherein the adaptive biomechanical model data is determined by changing the boundary conditions of the finite element model or the coupled spring model, respectively by moving nodes, changing or adding or deleting mass points, or changing or adding or deleting forces.

11. The method according to claim 1, wherein The initial biomechanical model data has been generated based on an atlas-based segmentation of patient image data of a digital medical image depicting the anatomical body part.

12. The method according to claim 1, wherein The anatomical body part includes at least a portion of the brain or at least a portion of the liver.

13. The method according to claim 1, wherein The patient state change is a change in at least one of the following: the position or geometry of the patient's body, or the relative position between the medical instrument and the patient's body, or the relative position between the medical personnel and the patient's body; the time between at least one of the above position changes; the configuration or use of the medical instrument; the time interval for the medical instrument to reach a specific position, or the time interval from a predetermined time point in the process.

14. The method according to claim 1, comprising: acquiring tracking data describing a medical entity, including a location of at least one of a patient, a medical personnel, or a medical instrument; obtaining workflow step definition data, the workflow step definition data describing an association between a medical entity, including at least one location of at least one of a patient, a medical person, or a medical instrument, and at least one workflow step of a procedure to be performed on the patient; Based on the tracking data and the workflow step definition, the workflow step data is obtained by comparing the location described by the tracking data with the workflow step definition data, and selecting at least one workflow step associated with the medical entity location corresponding to the location of the medical entity described by the tracking data as the current workflow step.

15. The method according to claim 14, wherein The tracking data is generated by imaging at least one medical entity, the at least one medical entity comprising at least one of the patient, the anatomical body part, a medical person, or a medical instrument.

16. The method according to claim 14, wherein The tracking data is generated by optically or electromagnetically tracking at least one marker device attached to at least one medical entity, the at least one medical entity comprising at least one of the patient, the anatomical body part, a medical person, or a medical instrument. 17 . A computer-readable storage medium storing a program including instructions, wherein when a computer executes the program, the instructions cause the computer to execute the method according to claim 1 .

18. A medical system (13), comprising: a) at least one computer (14) comprising at least one processor and a computer-readable storage medium according to claim 17; b) at least one electronic data storage device (15) storing at least the initial biomechanical model data and the model adaptability data; as well as c) a medical device (16) for performing a medical procedure on said patient, The at least one computer (14) is operably coupled to the at least one electronic data storage device (15) for obtaining at least the initial biomechanical model data and the model adaptability data from the at least one data storage device, and for storing the adaptive biomechanical model data in the at least one electronic data storage device (15).

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