Balancing Cohort Size and Variability in Iterative Deep Brain Template Creation

Most studies conducting probabilistic mapping of the effect of deep brain stimulation (DBS) use an external anatomical reference such as those of the MNI (Montreal Neurological Institute, [1]), alternatively, group-specific templates can be generated to avoid external anatomical bias. This study investigates the effect of cohort size on the creation of such anatomical references for movement disorders. Pre-operative MRI data from 70 patients implanted with DBS systems were used to generate anatomical templates with varying cohort sizes (5 to 67 subjects). An iterative non-linear normalization pipeline was employed to optimize template generation. Template variability was assessed using Dice overlap of anatomical structures. The templates created with 44 subjects achieved an optimal balance between variability and precision. Tukey's HSD test confirmed significant differences between iterations and cohort sizes. This study underscores the importance of cohort size and iterative registration methods in creating high-quality anatomical templates.Clinical relevance- The findings provide insights into the optimal cohort size for creating group-specific anatomical brain templates.