Aarhus University Seal / Aarhus Universitets segl

Post-operative deep brain stimulation assessment: Automatic data integration and report generation

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review



  • Andreas Husch, Centre Hospitalier de Luxembourg, University of Luxembourg
  • ,
  • Mikkel V. Petersen
  • Peter Gemmar, University of Luxembourg
  • ,
  • Jorge Goncalves, University of Luxembourg
  • ,
  • Niels Sunde
  • ,
  • Frank Hertel, Centre Hospitalier de Luxembourg, University of Luxembourg

Background: The gold standard for post-operative deep brain stimulation (DBS) parameter tuning is a monopolar review of all stimulation contacts, a strategy being challenged by recent developments of more complex electrode leads. Objective: Providing a method to guide clinicians on DBS assessment and parameter tuning by automatically integrating patient individual data. Methods: We present a fully automatic method for visualization of individual deep brain structures in relation to a DBS lead by combining precise electrode recovery from post-operative imaging with individual estimates of deep brain morphology utilizing a 7T-MRI deep brain atlas. Results: The method was evaluated on 20 STN DBS cases. It demonstrated robust automatic creation of 3D-enabled PDF reports visualizing electrode to brain structure relations and proved valuable in detecting miss placed electrodes. Discussion: Automatic DBS assessment is feasible and can conveniently provide clinicians with relevant information on DBS contact positions in relation to important anatomical structures.

Original languageEnglish
JournalBrain Stimulation
Pages (from-to)863-866
Number of pages4
Publication statusPublished - Jul 2018

    Research areas

  • Brain atlas, Computer aided surgery, Deep brain stimulation, Image registration, Post-operative assessment, Subthalamic nucleus

See relations at Aarhus University Citationformats

Download statistics

No data available

ID: 150202018