Simulating a Target Coverage for Deep Brain Stimulation

US2017177827A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2017177827-A1
Application numberUS-201715431575-A
CountryUS
Kind codeA1
Filing dateFeb 13, 2017
Priority dateDec 16, 2015
Publication dateJun 22, 2017
Grant date

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Abstract

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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: a) acquiring patient image data describing a medical image of the anatomical body part of a patient, wherein the anatomical body part includes the target anatomical structure b) acquiring atlas data describing a model of the anatomical body part and information about the position of a model target structure in the model of the anatomical body part, the model target structure corresponding to the target anatomical structure; c) determining, 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; d) acquiring, electrode position data describing a relative position between a position of an electrode and a position of the anatomical body part of the patient as it is described by the patient image data; e) acquiring stimulation field data describing an electric stimulation field around the position of the electrode; f) determining, based on the patient image data and the atlas data and the electrode position data and the stimulation field data, target coverage data describing a coverage of the target anatomical structure by the electric stimulation field.

First claim

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1 . 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: a) acquiring, at the at least one processor, patient image data describing a medical image of the anatomical body part of a patient, wherein the anatomical body part includes the target anatomical structure; b) acquiring, at the at least one processor, atlas data describing a model of the anatomical body part and information about the position of a model target structure in the model of the anatomical body part, the model target structure corresponding to the target anatomical structure; c) determining, by the at least one processor and 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; d) acquiring, at the at least one processor, electrode position data describing a relative position between a position of an electrode and a position of the anatomical body part of the patient as it is described by the patient image data; e) acquiring, at the at least one processor, stimulation field data describing an electric stimulation field around the position of the electrode; f) determining, by the at least one processor and based on the patient image data and the atlas data and the electrode position data and the stimulation field data, target coverage data describing a coverage of the target anatomical structure by the electric stimulation field. 2 . The method according to claim 1 , wherein the model of the anatomical body part is an image-based model. 3 . The method according to claim 1 , wherein determining the target structure position data includes determining, by the at least one processor and based on the patient image data and the atlas data, body part transformation data describing a positional transformation between the medical image of the anatomical body part and the model of the anatomical body part, and wherein the target coverage data is determined further based on the body part transformation data. 4 . The method according to claim 3 , wherein the body part transformation data is determined by applying an image fusion algorithm to the patient image data and the atlas data. 5 . The method according to claim 1 , wherein the electrode is a directional electrode having a plurality of electrically emitting contacts, and wherein the electric stimulation field is adjusted by adjusting a distribution of electric energy onto the contacts. 6 . The method according to claim 3 , further comprising: acquiring, at the at least one processor, electrode image data describing a second medical image of the electrode in the anatomical body part of the patient and specifically a relative position between the position of the electrode and the position of the anatomical body part in the second medical image; determining, by the at least one processor and based on the electrode image data and the atlas data, electrode transformation data describing a positional transformation between the position of the anatomical body part as it is described by the second medical image and the position of the model of the anatomical body part; wherein the electrode position data is determined, by the at least one processor, based on the electrode image data and the electrode transformation data and the body part transformation data. 7 . The method according to claim 6 , wherein the electrode transformation data is determined by applying an image fusion algorithm to the electrode image data and the atlas data. 8 . The method according to claim 6 , wherein the model of the anatomical body part is suitable for comparison with medical image data taken with two different medical imaging modalities, wherein the atlas data describes a multi-modal atlas of the anatomical body part. 9 . The method according to claim 8 , further comprising: determining, by the at least one processor and based on the patient image data and the target structure position data and the electrode position data, electrode target data describing a relative position between the position of the target anatomical structure and the position of the electrode; wherein the target coverage data is determined further based on the electrode target data. 10 . The method according to claim 1 , further comprising: acquiring, at the at least one processor, desired coverage data describing a desired coverage of the target anatomical structure by the electric stimulation field; determining, by the at least one processor, coverage difference data describing a difference between the coverage described by the target coverage data and the coverage described by the desired coverage data; varying, by the at least one processor, the stimulation field data in order to optimize the difference. 11 . The method according to claim 1 , wherein the stimulation field data is acquired based on user input. 12 . The method according to claim 11 , wherein the user input is manual input of the physical values defining the electric stimulation field. 13 . A non-transitory computer readable storage medium on which a program is stored, which, when executed by at least one processor, causes the at least one processor to perform the steps of: a) acquiring patient image data describing a medical image of the anatomical body part of a patient, wherein the anatomical body part includes the target anatomical structure; b) acquiring atlas data describing a model of the anatomical body part and information about the position of a model target structure in the model of the anatomical body part, the model target structure corresponding to the target anatomical structure; c) determining, 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; d) acquiring electrode position data describing a relative position between a position of an electrode and a position of the anatomical body part of the patient as it is described by the patient image data; e) acquiring stimulation field data describing an electric stimulation field around the position of the electrode; f) determining, based on the patient image data and the atlas data and the electrode position data and the stimulation field data, target coverage data describing a coverage of the target anatomical structure by the electric stimulation field. 14 . A system for determining a coverage of a target anatomical structure by an electric stimulation field, the system comprising: a) at least one electronic data storage device storing at least one database comprising: patient image data describing a medical image of the anatomical body part of a patient, wherein the anatomical body part includes the target anatomical structure, atlas data describing a model of the anatomical body part and information about the position of a model target structure in the model of the anatomical body part, the model target structure corresponding to the target anatomical structure, and electrode position data describing a relative position between a position of an electrode and a position of the anatomical body part of the patient as it is described by the patient image data; b) a computer including at least one processor that executes instructions stored on a computer readable storage medium to: acquire, from the at least one database, the patient image data and the atla

Assignees

Inventors

Classifications

  • Aspects of the external programmer · CPC title

  • providing test stimulations · CPC title

  • for handling medical images, e.g. DICOM, HL7 or PACS · CPC title

  • for simulation or modelling of medical disorders · CPC title

  • Selection of the electrode configuration · CPC title

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What does patent US2017177827A1 cover?
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: a) acquiring patient image data describing a medical image of the anatomical body part of a patient, wherein the anatomical body part includes the target an…
Who is the assignee on this patent?
Brainlab Ag
What technology area does this patent fall under?
Primary CPC classification G06F19/3437. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Jun 22 2017 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 1 related publication on this page (citations in our corpus or others sharing the same primary CPC).