Brainlab Ag

Bálint Varkuti

Stefan Achatz

Andreas Blumhofer

Rainer Lachner

Stefan Vilsmeier

Jens Schmaler

Stephan Mittermeyer

Harald Braun

Bogdan Moldovan

Christian Harrer

A computer-assisted and automatic identification of possible cranial positions for any kind of implant is presented. In this method, skull data of the individual patient's skull are used as well as statistical skull data which include so-called skull avoidance zones. Further, a digital template of the implant is used to find these possible positions. The implant may be e.g. an IPG and/or the screws of a fixation frame, but these are only embodiments of implants and other implants may be used with the present invention as well. The computer-implemented medical method of the present invention removes the uncertainty whether a given patient can safely receive an implant, like for example a cranial IPG, which was previously only possible on the basis of human judgement. Furthermore, the present invention removes the uncertainty whether a given patient can be safely fixated in a stereotactic frame or a Mayfield head clamp. The present invention supports the localization of optimal implant location as well as neuro-navigation guided execution of surgery. This enhances safety and speed of the entire medical procedure, as will be explained in more detail hereinafter. The advantages described hereinbefore are in the same way realized by the computer program, the medical system and the navigation system for computer-assisted surgery of the present invention.

Automated pre-operative assessment of implant placement in human bone

A medical data processing method is provided and includes: acquiring medical image data describing a digital image of an anatomical body part containing at least one nerve fibre extending between an internal part of the anatomical body part and a substantially exterior part of the anatomical body part; and acquiring atlas data describing an image-based model of the anatomical body part. The method determines, based on the medical image data and the atlas data, exterior part data describing an association between the exterior part and the nerve fibre. The method further acquires a predetermined applied stimulation signal applied to, based on the exterior part data, the exterior part and an emitted stimulation signal emitted by the nerve fibre. Correspondence measure data describing a measure of correspondence between the applied stimulation signal and the emitted stimulation signal is then determined.

Time-synchronized deep brain stimulation optimization

A system is disclosed for determining a coverage of a target anatomical structure by an electric stimulation field. The system includes a computer to acquire patient image data and the atlas data, determine, based on the patient image data and the atlas data, target structure position data describing a position of the target anatomical structure in the medical image of the anatomical body part of the patient. The system also acquires electrode position data and stimulation field data describing an electric stimulation field around the position of the electrode. The system also includes an electrode configuring device for adjusting an emission configuration of the electrode.

Simulating a target coverage for deep brain stimulation

During a sEEG (stereo-electroencephalography) intervention into the skull of a patient, there is requirement to drill a large number of trajectories. Typically, instrument stabilisation platforms and robots for protocols requiring only one or two trajectories are rigidly fixed to the skull using surgical anchor members fixed into the skull around the one or two trajectories. However, because sEEG interventions require a large number of trajectories, an impractical number of surgical anchor members need to be fixed into the skull resulting in patient discomfort. Attachment of an intervention platform to all surgical anchor members is not required at once. Accordingly, it is proposed to search for intersection points of the maximum extent of an intervention platform between at least two trajectory entry points on an object of interest of patient, so that at least one surgical anchor member can be shared when the intersection point is at first and the second trajectories. Any reduction in the number of surgical anchor members inserted into a patient reduces risk and discomfort. The positioning of the shared anchor members can be optimised to enable good mechanical stability, and/or optical registration performance. Furthermore, the number of surgical anchor members required for intervention can be reduced. Because the surgical anchor members are sterilised and made from high quality metal, a cost for performing the procedure can also be reduced.

Planning of surgical anchor placement location data

A method is provided for determining an orientation of nerve fibres relative to a non-physiological electric field. Patient medical image data is acquired, which describes a patient medical image of an anatomical body part of a patient's body. The anatomical body part includes nerve tissue comprising white matter nerve fibres. Diffusion image data is acquired, which describes a diffusion-enhanced image of the anatomical body part. Atlas data is acquired, which describes a spatial distribution of grey value-based tissue classes in a model body part representing a model of the anatomical body part. Based on the patient image data, the diffusion image data, and the atlas data, fibre orientation data is determined. The fibre orientation data describes an orientation of the white matter nerve fibres. Electric field orientation data is acquired, which describes an orientation of the non-physiological electric field. The non-physiological electric field is an electric field simulated around a simulated electrode virtually placed in a predetermined spatial relationship relative to the anatomical body part. Based on the fibre orientation data and the electric field orientation data, relative orientation data is determined. The relative orientation data describes a relative orientation between the orientation of the white matter nerve fibres and the orientation of the electric field.

Tissue-orientation-based simulation of deep brain stimulation

Disclosed is a computer-implemented medical data processing method for planning a position of an electric stimulation device for neurostimulation of at least two target regions (TV, . . . , TVN) disposed in an anatomical body part of a patient's body, the electric stimulation device () comprising at least two electric contacts, the method comprising executing, on at least one processor of at least one computer (), steps of: a) acquiring (S), at the at least one processor, medical image data describing a digital image of the anatomical body part, wherein the anatomical body part contains at least two target regions (TV, . . . , TVN); b) determining (S), by the at least one processor and based on the medical image data, target position data describing a position of each target region (TV, . . . , TVN) in the anatomical body part; c) acquiring (S), at the at least one processor, electric stimulation device geometry data describing a distance between the at least two contacts of the electric stimulation device (); d) determining (S), by the at least one processor and based on the target position data, target distance data describing a distance between each pair of the at least two target regions; e) determining (S), by the at least one processor and based on the target position data and the target distance data and the electric stimulation device geometry data, electric stimulation device position data describing a stimulation position which is a relative position between the at least two target regions (TV, . . . , TVN) and the electric stimulation device () which allows for stimulation of the at least two target regions (TV, . . . , TVN) by the electric stimulation device ().

Optimal deep brain stimulation electrode selection and placement on the basis of stimulation field modelling

The invention relates to a computer-implemented medical data processing method for determining a heartbeat signal describing the heartbeat of a patient in the time domain, the method comprising executing, on a processor of a computer, steps of: a) acquiring, at the processor, acceleration measurement data describing an acceleration in the time domain of an anatomical body part measured on an external surface of the anatomical body part; b) determining, by the processor, component analysis data describing a result of an independent component analysis in the time domain of the acceleration measurement data; c) acquiring, at the processor, heartbeat template data describing template shapes of heartbeat in the time domain; d) determining, by the processor and based on the component analysis data and the heartbeat template data, recurrent shape data describing a recurrence of certain signal shapes in the component analysis data; e) determining, based on the recurrent shape data, heartbeat signal data describing a time series of the heartbeat.

Detection of the heartbeat in cranial accelerometer data using independent component analysis

The present invention relates to a medical data processing method of determining an outcome quality of a medical procedure, the method comprising the following steps which are constituted to be executed by a computer: a) acquiring (S) pre-completion medical image data describing an anatomical structure of a patient's body in a state before the medical procedure has been completed on the anatomical structure, the anatomical structure being subject to the medical procedure; b) acquiring (S) pre-completion non-image medical data describing a state and medical history of the patient before the medical procedure has been completed on the anatomical structure; c) acquiring (S) medical procedure planning data describing a plan for execution of the medical procedure to be carried out on the anatomical structure; d) determining (S), based on the pre-completion medical image data and the medical procedure planning data, procedure application describing an application of the medical procedure planning data to the pre-completion medical image data; e) acquiring (S) post-completion non-image medical data describing a state and medical history of the patient after the medical procedure has been completed on the anatomical structure; f) acquiring (S) post-completion medical image data describing the anatomical structure in a state after the medical procedure has been completed on the anatomical structure; g) determining (S, S), based on the procedure application data and the pre-completion non-image medical data and the post-completion non-image medical data and the post-completion medical image data, outcome quality data comprising a quality measure describing a quality of the outcome of the medical procedure, the quality measure for example being specific to the indication in question, properties of the patient and the executive medical entity.

Determining medical outcome quality

Disclosed is a computer-implemented method for determining a coverage of a target anatomical structure by an electric stimulation field, the method comprising executing, on at least one processor of at least one computer, steps of:

The present disclosure sets forth a guiding tube for placing medical implants within body tissue. The guiding tube includes an elongated, dimensionally stable tubular body encompassing an inner channel adapted to receive a medical implant wherein the tubular body has at least one electromagnetic element, the element configured to exert an electromagnetic force on at least one magnetic element of the medical implant inserted into the inner channel of the guiding tube. The medical implant includes a stimulation lead having at least one directional electrode with an elongated body insertable into an inner channel enclosed by a tubular body of the guiding tube.

Electromagnetic guiding tube for elongated medical implants

The present invention relates to positioning a patient's body part including a target relative to an imaging device that generates a radiation beam directed towards the target. Geometry data is received that describes the geometry of at least one structure located in the field of view of the imaging device. Tracking date is received that describes the spatial location and/or orientation of the at least one structure within the field of view of the imaging device. Position data is determined that incorporates the geometry date and the tracking data. The position data describes whether the location and/or orientation of the at least one structure with respect to an image trajectory is desirable. Repositioning data is determined that describes a desired location and/or orientation of the at least one structure with respect to the image trajectory. The repositioning data is output to allow repositioning of the at least one structure.

Method for optimising the position of a patient's body part relative to an imaging device

The invention relates to a computer-implemented medical data processing method for determining a mapping of medical image content into a reference system, the method comprising executing, on a processor of a computer, steps of: a) acquiring, at the processor, medical image data describing a digital medical image of an anatomical structure of a patient's body; b) acquiring, at the processor, image attribute data describing attribute information associated with the medical image data, the attribute information including an indication of an initial reference system in which spatial relationships of the digital medical image are defined; c) acquiring, at the processor, reference system transformation data describing a spatial relationship (REG) between the initial reference system and a second reference system which is different from the initial reference system; d) determining, by the processor and based on the medical image data and the reference system transformation data, transformed image data describing a representation of the digital medical image in the second reference system.

Adaptation of image data sets to an updated atlas-based reference system

A computer implemented method of matching a medical images of an anatomical structure of a patient's body with an atlas-based representation of the anatomical structure is described. The method includes acquiring patient image data; determining, based on the patient image data, patient substructure data; acquiring general substructure data; determining, for each of the patient substructures and based on the patient substructure data and the general substructure data, substructure matching data; determining, based on the general substructure data and the substructure matching data, anatomical structure atlas data; determining, based on the patient image data and the anatomical structure atlas data, matching transformation data describing an atlas-patient matching transformation between the medical image representation of the anatomical structure and the atlas representation of the anatomical structure.

Generation of a patient-specific anatomical atlas

1. A medical data processing method of determining information describing the probable position of a neural fiber in a patient's brain, the method comprising the following steps which are constituted to be executed by a computer: a) acquiring patient-specific medical image data describing the brain of the patient; b) acquiring atlas data defining an image-based model of a human brain; c) determining, based on the patient-specific medical image data and the atlas data, seed region data describing seed regions (A, B) in the patient-specific medical image data in which the ends of neural fibers of the patient's brain may be located; d) determining, based on the patient-specific medical image data and the seed region data, neural fiber tract data describing a plurality of potential tracts (T, T, T) which a specific neural fiber may take through the patient's brain; e) determining, based on the atlas data and the neural fiber tract data, a figure of merit for each one of the potential tracts (T, T, T).

Growing community of inventors

Munich, Germany

Bálint Varkuti