IP Library › Granted Patent US 12,303,204
Granted Patent B2
US 12,303,204 · App. 17/260,096 · Granted May 20, 2025

Automated pre-operative assessment of implant placement in human bone

Inventors: Bálint Varkuti (Munich, DE); Bogdan Moldovan (Munich, DE)
Assignee: BRAINLAB AG
A61B34/10A61B34/25A61B90/14A61N1/37514G06T7/11G06T19/20G06V40/10G16H10/60G16H15/00G16H20/30G16H20/40G16H30/20G16H30/40G16H40/63G16H50/30A61B2034/104A61B2034/105G06T2207/20128G06T2210/41G06T2219/2012G06V2201/033
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Quick Facts
Patent No.
US 12,303,204
App. No.
17/260,096
Granted
May 20, 2025
Kind
B2
Abstract

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.

Claims (81)

1. A computer-implemented medical method of identifying a cranial position for an implant in a patient's skull, the method comprising the following steps:

acquiring an individual patient data set which describes a bone thickness and/or a bone density of the patient's skull,

acquiring statistical skull data including skull avoidance zones in which preferably no implant shall be implanted,

wherein the skull avoidance zones at least include one or more statistically derived zones describing a typical position and/or a size of an inter-individually variable head anatomy,

acquiring a digital template data set which geometrically describes at least one implant, and

automatically identifying a possible cranial position on the patient's skull for the at least one implant based on the individual patient data set and the statistical skull data thereby using the geometrical description of the at least one implant,

wherein the statistical skull data defines geometrical constraints or limitations describing geometric areas of a statistical human skull based on a plurality of individuals, which are excluded for the identification of said possible cranial position.

2. The method according to claim 1 ,

wherein the step of automatically identifying the possible cranial position on the patient's skull comprises a 3-dimensional template fitting of the at least one implant.

3. The method according to claim 1 , the method further comprising the following step

retrieving a minimum skull thickness under the implant required to maintain stable skull properties, and/or

retrieving a minimum skull thickness required to hold the implant for skull fixation.

4. The method according to claim 3 , the method further comprising the following steps

determining at least one continuous segment of the skull in which the retrieved minimum skull thickness is met, and

carrying out the step of automatically identifying the possible cranial position on the patient's skull only in said at least one determined segment meeting the minimum skull thickness.

5. The method according to claim 1 ,

wherein the individual patient data set and the statistical skull data are provided in form of image data, and the method further comprising the step

superimposing the individual patient data set with the statistical skull data in form of an image fusion of the individual patient data set and the statistical skull data.

6. The method according to claim 1 , the method further comprising the following step

displaying the respectively identified the possible cranial position on a user interface, preferably using color coding in a graphical representation of the patient's skull.

7. The method according to claim 1 , the method further comprising the following steps

acquiring CT images, MRI images and/or at least one other medical image from the patient,

extracting the patient's skull from the acquired images based on auto-segmentation, and

generating the individual patient data set by determining the bone thickness and/or the bone density of the extracted patient's skull.

8. The method according to claim 1 , the method further comprising the following steps

inquiring a user input about which implant or implants are available for implantation in the individual case of the patient, and

providing digital templates of the available implants within the digital template data set.

9. The method according to claim 1 ,

wherein the identified possible cranial position on the patient's skull are outside the skull avoidance zones defined in the statistical skull data.

10. The method according to claim 1 ,

wherein the skull avoidance zones at least include a muscle area at the lateral side of the skull, a zone on the back of the skull where the skull would have contact with a bed in a lying position of the patient, a zone of the skull along which the typical hairline extends, and/or one or more statistically derived zones describing a typical position and/or a size of the inter-individually variable frontal sinus.

11. The method according to claim 1 , the method further comprising the following steps

acquiring at least one of the following parameters which describe the individual patient: age, medical condition, ethnicity, type of skull, gender, and a phenotype parameter describing the skull, and

wherein for the step of acquiring the statistical skull data said acquired parameter or parameters describing the individual patient are taken into account.

12. The method according to claim 1 , the method further comprising the following steps

determining whether the patient's skull comprises open or closed fontanelles, and

using a result of the determination about the fontanelles during the step of identifying the possible cranial position.

13. The method according to claim 1 , the method further comprising the following step

determining whether the patient's skull contains calcifications, and

using a result of the determination about the calcifications during the step of identifying the possible cranial position.

14. The method according to claim 1 ,

wherein the implant is embodied as an Implantable Pulse Generator (IPG), an IPG having a non-planar, curved shape at a side facing the patient's skull when being implanted, an individualized IPG having a geometrical shape that is adapted to a shape of the individual patient's skull, or as a responsive neurostimulation (RNS) device.

15. The method according to claim 1 , the method further comprising the following additional step

automatically identifying the possible cranial position on the patient's skull for placing a fixation frame and/or a head clamp at the patient's skull thereby taking into account the previously identified possible cranial position for the at least one implant.

16. The method according to claim 1 , the method further comprising the following step

acquiring a user input about the kind of available IPGs as implants, in particular whether a rechargeable or a non-rechargeable IPG is available.

17. The method according to claim 14 , the method further comprising the following step

generating an output signal representative of a suggestion to a user containing which IPG shall be used at which position of the patient's skull or alternatively in an abdominal or chest area of the patient.

18. The method according to claim 1 ,

wherein the implant is embodied as a plurality of fixation screws for fixing a fixation frame at the patient's skull, and the method further comprising the following step

automatically identifying the possible cranial position on the patient's skull for each screw based on the individual patient data set and the statistical skull data thereby using geometrical descriptions of the screws.

19. The method according to claim 1 , the method further comprising the following step

acquiring a clinical report about the possible cranial position identified in a first iteration of the method and finally used by a user and taking said clinical report into account in a further iteration of the claimed method.

20. The method according to claim 1 , the method further comprising the following step

transferring data representative of the automatically identified possible cranial position and/or data representative of a user selection out of the automatically identified possible cranial position to a medical navigation system and/or an Augmented Reality display.

21. A non-transitory computer readable storage medium comprising instructions that when executed on at least one processor of at least one computer, causes the at least one computer to perform the steps of:

acquiring an individual patient data set which describes a bone thickness and/or a bone density of the patient's skull;

acquiring statistical skull data including skull avoidance zones in which preferably no implant shall be implanted;

wherein the skull avoidance zones at least include one or more statistically derived zones describing a typical position and/or a size of an inter-individually variable head anatomy,

acquiring a digital template data set which geometrically describes at least one implant, and

automatically identifying a possible cranial position on the patient's skull for the at least one implant based on the individual patient data set and the statistical skull data thereby using the geometrical description of the at least one implant;

wherein the statistical skull data defines geometrical constraints or limitations describing calculated geometric areas of a statistical human skull based on a plurality of individuals, which are excluded for the identification of said possible cranial position.

22. A medical system, comprising:

at least one computer having at least one processor and associated memory, the memory storing instructions which when executed cause the at least one processor to:

acquire an individual patient data set which describes a bone thickness and/or a bone density of the patient's skull;

acquire statistical skull data including skull avoidance zones in which preferably no implant shall be implanted;

wherein the skull avoidance zones at least include one or more statistically derived zones describing a typical position and/or a size of an inter-individually variable head anatomy,

acquire a digital template data set which geometrically describes at least one implant, and

automatically identify a possible cranial position on the patient's skull for the at least one implant based on the individual patient data set and the statistical skull data thereby using the geometrical description of the at least one implant;

wherein the statistical skull data defines geometrical constraints or limitations describing calculated geometric areas of a statistical human skull based on a plurality of individuals, which are excluded for the identification of said possible cranial position;

at least one electronic data storage device storing at least data describing the identified possible cranial position; and a medical device for carrying out a medical procedure on the patient, wherein the at least one computer is operably coupled to:

the at least one electronic data storage device for acquiring, from the at least one data storage device, at least the data describing the identified possible cranial position, and

the medical device for issuing a control signal to the medical device for controlling the operation of the medical device on the basis of the data describing the identified possible cranial position.

23. A computer-implemented medical method of identifying a cranial position for an implant in a patient's skull, the method comprising the following step:

acquiring an individual patient data set which describes a bone thickness and/or a bone density of the patient's skull,

acquiring statistical skull data including skull avoidance zones in which preferably no implant shall be implanted,

wherein the skull avoidance zones at least include one or more statistically derived zones describing a typical position and/or a size of an inter-individually variable head anatomy,

acquiring a digital template data set which geometrically describes at least one implant, and

automatically identifying a possible cranial position on the patient's skull for the at least one implant based on the individual patient data set and the statistical skull data thereby using the geometrical description of the at least one implant,

wherein the statistical skull data defines geometrical constraints or limitations describing calculated geometric areas of a statistical human skull based on a plurality of individuals, which are excluded for the identification of said possible cranial position, and

wherein the skull avoidance zones comprise at least one of: sides of the skull where muscles are located, the back of the skull, information that can be used describing the typical or individual hairline position to avoid aesthetic disfigurement, and statistical information on typical position and/or size of the inter-individually variable frontal sinuses.

Assignments (2)
CHANGE OF NAME Recorded Aug 4, 2025
From: BRAINLAB AG
To: BRAINLAB SE
Reel/Frame 071922/0615 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 8, 2021
From: VARKUTI, BÁLINT; MOLDOVAN, BOGDAN
To: BRAINLAB AG
Reel/Frame 055182/0268 →
Continuity (1)
Related Publication 20210322101A1 · Oct 21, 2021
References Cited (27)
US 6086533A · Madsen · 2000 [cited by examiner]
US 7783359B2 · Meadows · 2010 [cited by applicant]
US 9165360B1 · Bates · 2015 [cited by examiner]
US 9492241B2 · Joskowicz · 2016 [cited by examiner]
US 20020013612A1 · Whitehurst · 2002 [cited by applicant]
US 20040172090A1 · Janzig et al. · 2004 [cited by applicant]
US 20050245806A1 · Singhal · 2005 [cited by examiner]
US 20070225773A1 · Shen et al. · 2007 [cited by applicant]
US 20090177081A1 · Joskowicz · 2009 [cited by examiner]
US 20190214126A1 · Goetz · 2019 [cited by examiner]
US 20200043168A1 · Tanji · 2020 [cited by examiner]
WO 2006075331 · 2006 [cited by applicant]
WO 2006092600 · 2006 [cited by applicant]
WO 2010068212 · 2010 [cited by applicant]
WO 2015124199 · 2015 [cited by applicant]
WO 2017039762 · 2017 [cited by applicant]
WO 2019139690A1 · 2019 [cited by applicant]
WO 2020043291 · 2020 [cited by applicant]
Raudaschl, Patrik F., et al. “Evaluation of segmentation methods on head and neck CT: auto-segmentation challenge 2015.” Medical physics 44.5 (2017): 2020-2036. (Year: 2017). [cited by examiner]
Labadie, Robert Frederick, et al. “Clinical validation of percutaneous cochlear implant surgery: initial report.” The Laryngoscope 118.6 (2008): 1031-1039. (Year: 2008). [cited by examiner]
Powell, Kimerly A., et al. “Atlas-based segmentation of temporal bone anatomy.” International journal of computer assisted radiology and surgery 12 (2017): 1937-1944. (Year: 2017). [cited by examiner]
Metzger, Marc Christian, et al. “Design and development of a virtual anatomic atlas of the human skull for automatic segmentation in computer-assisted surgery, preoperative planning, and navigation.” International journ… [cited by examiner]
Faisan, Sylvain, et al. “Topology preserving warping of binary images: Application to atlas-based skull segmentation.” International Conference on Medical Image Computing and Computer-Assisted Intervention. Berlin, Heid… [cited by examiner]
Raudaschl, Patrik F., et al. “Evaluation of segmentation methods on head and neck CT: auto-segmentation challenge 2015.” Medical physics 44.5 (2017): 2020-2036. (Year: 2015). [cited by examiner]
Wimmer, Wilhelm, et al. “Topographic bone thickness maps for Bonebridge implantations.” European Archives of Oto-Rhino-Laryngology 272 (2015): 1651-1658. (Year: 2015). [cited by examiner]
International Search Report and Written Opinion for Application No. PCT/EP2018/073320 dated May 28, 2019. 12 pages. [cited by applicant]
European Patent Office; Communication issued in Application No. 18762285.7, 5 pages, dated Jun. 4, 2024. [cited by applicant]