Hemm-Ode, Simone

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Hemm-Ode
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Simone
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Hemm-Ode, Simone

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20202
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    Publikation
    Atlas Optimization for Deep Brain Stimulation
    (IFMBE, 30.11.2020) Vogel, Dorian; Wardell, Karin; Coste, Jérôme; Lemaire, Jean-Jaques; Hemm-Ode, Simone; Jarm, Tomaz; Cvetkoska, Aleksandra; Mahnič-Kalamiza, Samo; Miklavcic, Damijan [in: EMBEC 2020: 8th European Medical and Biological Engineering]
    Abstract : Electrical stimulation of the deep parts of the brain is the standard answer for patients subject to drug-refractory movement disorders. Collective analysis of data collected during surgeries are crucial in order to provide more systematic planning assistance and understanding the physiological mechanisms of action. To that end, the process of normalizing anatomies captured with Magnetic Resonance imaging across patients is a key component. In this work, we present the optimization of a workflow designed to create group-specific anatomical templates: a group template is refined iteratively using the results of successive non-linear image registrations with refinement steps in the in the basal-ganglia area. All non-linear registrations were executed using the Advanced Normalization Tools (ANTs) and the quality of the nor-malization was measured using spacial overlap of anatomical structures manually delineated during the planning of the surgery. The parameters of the workflow evaluated were: the use of multiple modalities sequentially or together during each registration to the template, the number of iterations in the template creation and the fine settings of the non-linear registration tool. Using the T1 and white matter attenuated inverse recovery modalities (WAIR) together produced the best results, especially in the center of the brain. The optimal numbers of iterations of the template creation were higher than those from the literature and our previous works. Finally, the setting of the non-linear registration tool that improved results the most was the activation of the registration with the native voxel sizes of images, as opposed to down-sampled version of the images. The normalization process was optimized over our previous study and allowed to obtain the best possible anatomical nor-malization of this specific group of patient. It will be used to summarize and analyze peri-operative measurements during test stimulation. The aim is that the conclusions obtained from this analysis will be useful for assistance during the planning of new surgeries.
    04B - Beitrag Konferenzschrift
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    Publikation
    Anatomical brain structures normalization for deep brain stimulation in movement disorders
    (Elsevier, 25.04.2020) Vogel, Dorian; Shah, Ashesh; Hemm-Ode, Simone [in: NeuroImage: Clinical]
    Deep brain stimulation (DBS) therapy requires extensive patient-specific planning prior to implantation to achieve optimal clinical outcomes. Collective analysis of patient’s brain images is promising in order to provide more systematic planning assistance. In this paper the design of a normalization pipeline using a group specific multi-modality iterative template creation process is presented. The focus was to compare the performance of a selection of freely available registration tools and select the best combination. The workflow was applied on 19 DBS patients with T1 and WAIR modality images available. Non-linear registrations were computed with ANTS, FNIRT and DRAMMS, using several settings from the literature. Registration accuracy was measured using single-expert labels of thalamic and subthalamic structures and their agreement across the group. The best performance was provided by ANTS using the High Variance settings published elsewhere. Neither FNIRT nor DRAMMS reached the level of performance of ANTS. The resulting normalized definition of anatomical structures were used to propose an atlas of the diencephalon region defining 58 structures using data from 19 patients.
    01A - Beitrag in wissenschaftlicher Zeitschrift