References of "Petersen, Mikkel V."
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See detailUsing automated electrode localization to guide stimulation management in DBS
Petersen, Mikkel V.; Husch, Andreas UL; Parsons, Christine E. et al

in Annals of Clinical and Translational Neurology (2018), 0(0),

Abstract Deep Brain Stimulation requires extensive postoperative testing of stimulation parameters to achieve optimal outcomes. Testing is typically not guided by neuroanatomical information on electrode ... [more ▼]

Abstract Deep Brain Stimulation requires extensive postoperative testing of stimulation parameters to achieve optimal outcomes. Testing is typically not guided by neuroanatomical information on electrode contact locations. To address this, we present an automated reconstruction of electrode locations relative to the treatment target, the subthalamic nucleus, comparing different targeting methods: atlas‐, manual‐, or tractography‐based subthalamic nucleus segmentation. We found that most electrode contacts chosen to deliver stimulation were closest or second closest to the atlas‐based subthalamic nucleus target. We suggest that information on each electrode contact's location, which can be obtained using atlas‐based methods, might guide clinicians during postoperative stimulation testing. [less ▲]

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See detailPaCER - A fully automated method for electrode trajectory and contact reconstruction in deep brain stimulation
Husch, Andreas UL; Petersen, Mikkel V.; Gemmar, Peter et al

in NeuroImage: Clinical (2018), 17

Abstract Deep brain stimulation (DBS) is a neurosurgical intervention where electrodes are permanently implanted into the brain in order to modulate pathologic neural activity. The post-operative ... [more ▼]

Abstract Deep brain stimulation (DBS) is a neurosurgical intervention where electrodes are permanently implanted into the brain in order to modulate pathologic neural activity. The post-operative reconstruction of the DBS electrodes is important for an efficient stimulation parameter tuning. A major limitation of existing approaches for electrode reconstruction from post-operative imaging that prevents the clinical routine use is that they are manual or semi-automatic, and thus both time-consuming and subjective. Moreover, the existing methods rely on a simplified model of a straight line electrode trajectory, rather than the more realistic curved trajectory. The main contribution of this paper is that for the first time we present a highly accurate and fully automated method for electrode reconstruction that considers curved trajectories. The robustness of our proposed method is demonstrated using a multi-center clinical dataset consisting of N=44 electrodes. In all cases the electrode trajectories were successfully identified and reconstructed. In addition, the accuracy is demonstrated quantitatively using a high-accuracy phantom with known ground truth. In the phantom experiment, the method could detect individual electrode contacts with high accuracy and the trajectory reconstruction reached an error level below 100 μm (0.046 ± 0.025 mm). An implementation of the method is made publicly available such that it can directly be used by researchers or clinicians. This constitutes an important step towards future integration of lead reconstruction into standard clinical care. [less ▲]

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See detailPost-operative deep brain stimulation assessment: Automatic data integration and report generation
Husch, Andreas UL; Petersen, Mikkel V.; Gemmar, Peter et al

in Brain Stimulation (2018)

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 ... [more ▼]

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. [less ▲]

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