Medical system and method for controlling medical data processing using current workflow steps

Abstract

The present disclosure relates to a computer-implemented method for adapting a biomechanical model of a patient's anatomical part to the patient's current state. The method includes determining a currently executed 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 part to the corresponding current patient state. Determining the current workflow step can also be used as a basis for controlling an imaging device to track entities surrounding the patient, or to image the anatomical part or acquire other data, or to prompt a user to perform a specific action, such as using a tracking instrument, such as a pointer, to acquire information. The biomechanical model is generated based on atlas data. The data set generated based on the current workflow step can be used additionally or alternatively as a basis for determining the current workflow step and / or adapting to another workflow.

Description

Technical Field

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

[0002] Biomechanical models are used, for example, to describe anatomical changes that may result from a medical intervention and to update patient image data used for planning and navigating the intervention accordingly. It is also known to base such updates on spatial sampling data generated during the intervention, such as medical image data. Summary of the Invention

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

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

[0005] The following discloses various aspects, examples and exemplary steps of the present invention and its embodiments. The different exemplary features of the present invention may be combined according to the invention whenever technically suitable and feasible.

[0006] Summary of the Invention

[0007] 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.

[0008] The method of the present disclosure includes determining a currently executed 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 part of the body to the corresponding current patient state. Determining the current workflow step can also be used as a basis for controlling an imaging device to track entities surrounding the patient, or to image or acquire other data of the anatomical part of the body, or to prompt a user to perform a specific action, such as using a tracking instrument, such as a pointer, to acquire information. The biomechanical model is generated based on the atlas data. The data set generated based on the current workflow step can be used additionally or alternatively as a basis for determining the current workflow step and / or adapting another workflow. SUMMARY OF THE INVENTION

[0010] In this section, a description of general features of the present invention is given, for example, by reference to possible embodiments of the invention.

[0011] In general, the present invention achieves the aforementioned objectives by, in a first aspect, providing a computer-implemented medical method for adapting a biomechanical model of a patient's anatomical region 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 navigation system).

[0012] In a (e.g., first) exemplary step, initial biomechanical model data is acquired, the initial biomechanical model data describing an initial biomechanical model of a body anatomical part. For example, the biomechanical model is a finite element model or a coupled spring model of the body anatomical part. For example, the adaptive biomechanical model data is determined by changing the boundary conditions of the finite element model or the coupled spring model, respectively, such as by moving nodes, changing or adding or deleting mass points, or changing or adding or deleting forces. For example, the initial biomechanical model data is generated based on an atlas-based segmentation of patient image data describing a digital medical image of the body anatomical part, i.e., by establishing a mapping between atlas data describing an image-based model of the body anatomical part and patient image data describing a digital medical image of the body anatomical part, so as to segment an image representation of the body anatomical part. For example, the body anatomical part includes at least a portion of the brain or at least a portion of the liver.

[0013] In a (e.g., second) exemplary step, workflow step data is obtained, the workflow step data describing a current workflow step of a procedure to be performed on a patient. For example, tracking data is obtained, the tracking data describing a location of at least one of a medical entity, i.e., a patient, a medical practitioner, or a medical instrument; and workflow step definition data is obtained, the workflow step definition data describing an association between at least one location of at least one of the medical entity, i.e., the patient, the medical practitioner, or the medical instrument, and at least one workflow step of the procedure to be performed on the patient. For example, the workflow step data is then obtained based on the tracking data and the workflow step definition data, by comparing the location described by the tracking data with the workflow step definition data and selecting, as the current workflow step, 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. For example, the tracking data is generated by imaging, e.g., video imaging, of at least one of the at least one medical entity, e.g., a patient, an anatomical part of a body, 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 of the at least one medical entity, e.g., a patient, an anatomical part of a body, a medical practitioner, or a medical instrument.

[0014] In a (e.g., third) exemplary 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 part of the body; or a relative position between a medical instrument and the patient's body, or a relative position between a medical staff member and the patient's body; a time interval between at least one of the position changes; 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.

[0015] In an exemplary (e.g., fourth) step, model adaptability data is obtained that describes a correlation between changes in the patient's state and adaptability to be applied to the initial biomechanical model. Adaptability is defined, for example, as a change 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.

[0016] In a (e.g., fifth) exemplary step, adaptive biomechanical model data are determined based on the initial biomechanical model data and 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.

[0017] In an example of a method according to the first aspect, region of interest data is acquired based on the state change data, wherein the region of interest data describes a region or trajectory within or on a process to be performed, such as the process described above, such as an anatomical region or an object surface. For example, the process includes acquiring instrument tracking data describing a position of a navigation instrument based on the region of interest data. Alternatively or additionally, the process includes acquiring video or medical image data describing at least a portion of a patient, such as an anatomical body part, based on the region of interest data. For example, the process includes acquiring medical image data and an imaging device, such as an ultrasound imaging probe, for generating the medical image data, handheld or manually guided, or automatically guided, such as by a robotic arm.

[0018] 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 acquire an image of at least a portion of an anatomical part of the body. For example, the portion of the anatomical part to be imaged depends on the type of state change of the patient. For example, the portion of the anatomical 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 part to be imaged.

[0019] 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., a physical, e.g., electrical, generated by technical means), e.g., a digital signal wave, such as an electromagnetic carrier wave, carrying information representing a program, e.g., the program described above, wherein the program, for example, comprises code means suitable for performing any or all of the steps of the method according to the first aspect. In one embodiment, 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, e.g., in the form of a physical, e.g., electrical, signal (e.g., 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, e.g., 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 of the program described above (i.e., including the program).

[0020] In a third aspect, the present invention relates to a computer-readable storage medium storing the program according to the second aspect. The program storage medium is, for example, non-transitory.

[0021] In a fourth aspect, the present invention relates to at least one computer (e.g., a computer) comprising at least one processor (e.g., a processor) and at least one memory (e.g., a memory), 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.

[0022] In a fifth aspect, the present invention relates to a medical system comprising:

[0023] a) at least one computer according to the fourth aspect;

[0024] b) at least one electronic data storage device storing at least initial biomechanical model data and model adaptation data; and

[0025] c) Medical devices used to perform medical procedures on patients.

[0026] At least one computer is operatively coupled to at least one electronic data storage device to retrieve at least initial biomechanical model data and model adaptation data from the at least one data storage device and to store the adapted biomechanical model data in the at least one data storage device.

[0027] In a sixth aspect, the present invention relates to the use of a system according to the preceding claim 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 a body anatomical part of a patient to the current patient state.

[0028] For example, the present invention does not involve or particularly does not include or encompass invasive procedures that represent a substantial physical disturbance of the body requiring professional medical care or intervention that may expose the body to significant health risks even with the required professional care or intervention.

[0029] definition

[0030] Definitions of certain terms used in this disclosure are provided in this section and also constitute a part of this disclosure.

[0031] The method according to the present invention is, for example, a computer-implemented method. For example, all or only some of the steps (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). An embodiment of a computer-implemented method is a method in which a computer is used to perform a data processing method. An embodiment of a computer-implemented method is a method involving computer operation such that the computer is operated to perform one, more, or all of the steps of the method.

[0032] 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 II, III, IV, V, VI semiconductor materials, for example (doped) silicon arsenide 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 a computer, such as a desktop personal computer, a laptop, a netbook, etc., but can also be any programmable device, such as a mobile phone or an embedded processor. A computer can, for example, include a system (network) of "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 a cloud computer system, which includes, for example, a system of at least one cloud computer and, for example, a plurality of operatively interconnected cloud computers, such as a server farm. Such a cloud computer is preferably connected to a wide area network, such as the World Wide Web (WWW), and is located in a so-called cloud of computers 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 a computing infrastructure as a service (IaaS). A cloud computer can be used as a virtual host for an operating system and / or data processing application for executing the method of the present invention. A cloud computer is, for example, provided by Amazon Web Services. TM) provided by the Elastic Compute Cloud (EC2). The computer, for example, includes an interface to receive or output data and / or perform analog-to-digital conversion. The data is, for example, data representing physical properties and / or generated from 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, for example, represent 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 navigation. 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, which is operatively connected to a computer for receiving display control data from the computer for generating signals for displaying the 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 the product of Brainlab AG The monitor may also be a handheld portable device such as a smartphone or a personal digital assistant or a digital media player, for example.

[0033] The present invention also relates to a computer program comprising instructions, which, when executed by a computer, cause the computer to perform one or more methods described herein, such as steps of one or more methods; and / or the present invention relates to a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium) storing the program; and / or the present invention relates to a computer comprising the program storage medium; and / or the present invention relates to a signal wave (e.g., a physical, e.g., electrical, generated by technical means), such as a digital signal wave, such as an electromagnetic carrier wave, carrying information representing a program (e.g., the above-mentioned program), the program for example comprising code means suitable for performing any or all of the method steps described herein. In one example, the signal wave is a data carrier signal carrying the above-mentioned computer program. The present invention also relates to a computer comprising at least one processor and / or the above-mentioned computer-readable storage medium and, for example, a memory, wherein the program is executed by a processor.

[0034] Within the scope of the present invention, a computer program element may be embodied in hardware and / or software (this includes firmware, resident software, microcode, etc.). Within the scope of the present invention, a computer program element may take the form of a computer program product, which may be implemented by 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 the computer program element, and optionally a 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 scope 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, device, or apparatus. Computer-usable, for example, 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 the program can be printed, since the program can be captured electronically, for example, by optically scanning the paper or other suitable media, and then compiled, decoded, 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 mechanisms for performing the functions of the present invention in the example embodiments. The computer and / or data processing device can, for example, include a guidance information device that includes a mechanism for outputting guidance information. The guidance information can, for example, be output to the user visually via a visual indication mechanism (e.g., a monitor and / or light) and / or auditorily via an auditory indication mechanism (e.g., a speaker and / or digital voice output device) and / or tactilely via a tactile indication mechanism (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, for example comprising technical components such as tangible components, for example mechanical components and / or electronic components. Any device mentioned in this document is a technical device and for example a tangible device.

[0035] The term "acquire data" encompasses, for example, the determination of data by a computer-implemented method or program (within the framework of the computer-implemented method). Determining data encompasses, for example, measuring a physical quantity and converting the measured value into data, such as digital data, and / or computing (e.g., outputting) the data using a computer, for example, within the framework of the method according to the present invention. The "determining" step, as described herein, encompasses, for example, issuing a command to perform a determination as described herein or consisting of the same. For example, the step comprises 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, the "determining" step, as described herein, encompasses, for example, receiving result data from a determination as described herein, such as from a remote computer (e.g., from the remote computer that caused the determination to be performed). "Acquire data" also encompasses, for example, the receipt or retrieval of data by a computer-implemented method or program (e.g., input), such as from another program, a previous method step, or a data storage medium, for example, 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, mean 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 mean that a method or program implemented by a computer performs some steps in order to (actively) receive or retrieve data from a data source such as a data storage medium (e.g., ROM, RAM, database, hard drive, etc.) or via an interface (e.g., from another computer or network). 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 to perform data transmission between the database and the computer, such as data transmission from a database to the computer. The computer obtains data to serve as input for the "determining data" step. The determined data can then be output to the same or another database to be stored for subsequent use. The database or the database for implementing the disclosed method can be located on a network data storage device or a network server (e.g., a cloud data storage device or cloud server) or a local data storage device (e.g., a mass storage device operably connected to at least one computer performing the disclosed method). The data can be made "ready" by performing an additional step before the acquisition step. According to this additional step, data is generated for acquisition. For example, data is detected or captured (eg, by an analysis device). Alternatively or additionally, data is input according to an additional step, such as via an interface. For example, the generated data can be input (eg, 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 (e.g., ROM, RAM, CD, and / or hard drive), thereby making the data available within the framework of the method or program according to the present invention. Therefore, the step of "acquiring data" can also involve instructing a device to acquire and / or provide the data to be acquired. In particular, the acquisition step does not involve an invasive step that represents a substantial physical disturbance of the body, requiring professional medical measures, and which, even when performed with the required professional care and measures, may expose the body to significant health risks. In particular, the step of acquiring data, such as determining the data, does not involve a surgical step, in particular, 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," etc., and are defined according to the information they describe, and are then preferably referred to as "XY information," etc.

[0036] 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 part of the body. Thus, the atlas data represents an atlas of an anatomical part of the body. An atlas typically consists of a plurality of general models of objects, wherein these general models of objects together form a composite structure. For example, an atlas constitutes a statistical model of a patient's body (e.g. a part of the 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 containing 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 corresponds 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 an 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 that, for example, the atlas data is compared with the medical image data in order to determine the position of anatomical structures in the medical image data that correspond to anatomical structures defined by the atlas data.

[0037] Multiple human bodies whose anatomical structures are used as input to generate atlas data advantageously share common features, such as at least one of gender, age, race, body measurements (e.g., height and / or weight), and pathological conditions. The anatomical information, for example, describes the anatomical structure of the human body and is, for example, extracted 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.

[0038] For example, the atlas data includes information about an anatomical part of the body. 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 part of the body relative to a given reference (e.g., another anatomical part of the body). For example, the atlas is a multimodal atlas that defines atlas information for multiple (i.e., at least two) imaging modalities and includes mappings between atlas information under different imaging modalities (e.g., mappings between all modalities) such that the atlases can be used to transform medical image information from its image depiction under a first imaging modality to its image depiction under a second imaging modality different from the first imaging modality, or to compare different imaging modalities with each other (e.g., matching or registration).

[0039] 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 (such as 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 radiographic methods), such as computed tomography (CT) and cone beam computed tomography (CBCT, such as volume CBCT), X-ray tomography, magnetic resonance tomography (MRT or MRI), conventional X-rays, ultrasonography and / or ultrasound verification, and positron emission tomography. For example, the medical imaging method is performed by an analysis device. Examples of medical imaging modalities used by the medical imaging method 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 thus generated 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 body anatomical structures to generate images described by the 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 detectable and may not be visible, for example, in images generated by the imaging method. A tumor represents an example of a change in the anatomical structure. If a tumor grows, it can be considered to represent an expanded anatomical structure. Such an expanded anatomical structure may not be detectable, 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 is detectable and discernible, for example, 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.

[0040] 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 (the basis of the second coordinate system being 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, as a transformation matrix (e.g., a matrix defining an affine transformation). BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Hereinafter, the present invention will be described with reference to the accompanying drawings, which provide an explanation of the background of the invention and show specific embodiments of the 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:

[0042] Figure 1 A basic flow chart of the method according to the first aspect is shown;

[0043] Figure 2 illustrating the application of the method according to the first aspect; and

[0044] Figure 3 is a schematic diagram of the system according to the fifth aspect. DETAILED DESCRIPTION

[0045] Figure 1 The basic steps of the method according to the first aspect are shown, wherein step S1 comprises obtaining initial biomechanical model data, step S2 comprises obtaining workflow step data, followed by step S3 comprising 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.

[0046] 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 11 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 (such as a microscope), or based on the intra-procedural data 8. 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. The image data generated using the tomograph 5 can also be used to determine the current workflow step. The current workflow step can also be used to initiate the operation of the video camera or tracking imaging device 2 used to generate the image data 1. The use of the tracking pointer 3 can also serve as a basis for determining the current workflow step.

[0047] Figure 3 1 is a schematic diagram of a medical system 13 according to the fifth aspect. The system is generally designated 13 and comprises a computer 14 and an electronic data storage device (such as 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.

[0048] The following exemplary aspects are also part of possible embodiments of the present invention.

[0049] - Initial biomechanical model data is generated based on the physical (eg mechanical) properties of tissue types (eg tissue classes) stored in the atlas.

[0050] - Workflow step data may be based on intraoperative image data (e.g., from an X-ray device, a fluoroscopy device, an X-ray tomography scanner, an MRI scanner, a C-arm), on intraoperative video data (e.g., from an endoscope, a microscope, an endoscope, or an external camera with a view of the surgical site), on ultrasound image data, on the position, velocity, and acceleration of an instrument or imaging device, e.g., as a function of time. Workflow step data may be based on the content of intraoperative video data, such as the position or velocity or acceleration of an instrument or implant or anatomical object in the image, e.g., as a function of time.

[0051] - The workflow step data may also be based on other intraoperative or in-procedural 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.

[0052] - 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.

[0053] 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 is, for example, based on 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.

[0054] The workflow step data may also be based on a stored workflow of the execution process type. Such a stored workflow comprises a number of predetermined steps.

[0055] - 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.

[0056] - Status change data includes, for example, dura opening, resection performed, and instrumentation in place.

[0057] - A handheld or manually guided or automatically guided imaging device such as an ultrasound probe, a microscope or an endoscope.

[0058] - 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 medical method for adapting a biomechanical model of an anatomical part of a patient's body to the patient's current condition, the method comprising the steps of: a) acquiring initial biomechanical model data, wherein the initial biomechanical model data describes an initial biomechanical model of the anatomical part of the body; b) acquiring tracking data describing the location of the medical entity; c) obtaining workflow step definition data, the workflow step definition data describing an association between at least one location of the medical entity and at least one workflow step of a procedure to be performed on the patient; d) obtaining workflow step data describing a current workflow step of a procedure to be performed on the patient, wherein the workflow step data is obtained based on the tracking data and the workflow step definition data, and wherein at least one workflow step associated with a medical entity location corresponding to the medical entity location described by the tracking data is selected as the current workflow step; e) determining state change data based on the workflow step data and the initial biomechanical model data, wherein the state change data describes a patient state change, wherein the patient state change is a relative position change between a medical entity and a patient's body; f) acquiring model adaptability data describing a correlation between a change in the patient's state and adaptability to be applied to the initial biomechanical model; g) determining adaptive biomechanical model data based on the initial biomechanical model data and the state change data and the model adaptability data, wherein the adaptive biomechanical model data describes an adaptive biomechanical model determined by applying adaptability to the initial biomechanical model.

2. The method according to claim 1, comprising the steps of: Area-of-interest data is acquired based on the state change data, wherein the area-of-interest data describes an area where a process is to be performed.

3. The method according to claim 2, wherein: The process includes: acquiring instrument position data based on the region of interest data, the instrument position data describing the position of a navigation instrument; or Medical image data is acquired based on the region of interest data, the medical image data describing at least a portion of the body anatomy.

4. The method according to claim 3, wherein: Handheld or manually guided or automatically guided imaging device for generating medical image data.

5. The method according to claim 4, comprising the steps of: Imaging control data is determined based on the state change data, wherein the imaging control data describes a command to be issued to the imaging device to acquire an image of at least a portion of the body anatomical part, wherein the portion to be imaged in the body anatomical part anatomically corresponds to a portion of the biomechanical model adapted to determine the adaptive biomechanical model data.

6. The method according to claim 5, wherein: The adaptive biomechanical model data is determined based on the latest image data.

7. The method according to claim 5, wherein: The imaging control data is transmitted to the imaging device and performed to determine medical image data describing a medical image of the portion of the body anatomy to be imaged.

8. The method according to claim 1, wherein The biomechanical model is a finite element model or a coupled spring model of the body anatomical part, and wherein the adaptive biomechanical model data is determined by changing boundary conditions of the finite element model or the coupled spring model.

9. The method according to claim 8, wherein The adaptive biomechanical model data is determined by moving nodes, changing or adding or deleting mass points, or changing or adding or deleting forces.

10. The method according to claim 1, wherein The initial biomechanical model data is generated based on atlas-based segmentation of patient image data describing a digital medical image of the body anatomical region.

11. 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. 12 . A computer-readable program storage medium comprising instructions, which, when executed by at least one processor of a computer, cause the at least one processor to perform the method according to claim 1 .

13. A medical system comprising: a) a computer, comprising instructions stored in a memory of the computer, which instructions, when executed by at least one processor of the computer, cause the at least one processor to perform the method according to any one of claims 1 to 11; b) at least one electronic data storage device storing at least said initial biomechanical model data and said model adaptability data; as well as c) medical devices used to perform medical procedures on patients, The computer is operatively coupled to the at least one electronic data storage device to retrieve at least the initial biomechanical model data and the model adaptability data from the at least one electronic data storage device and store the adapted biomechanical model data in the at least one electronic data storage device.

14. Use of the medical system according to claim 13 for performing a medical procedure, wherein: The use comprises performing the steps of the method according to any one of claims 1 to 11 in order to adapt the biomechanical model of the patient's body anatomy to the current patient state.

Images