Normative vs. patient-specific brain connectivity in Deep Brain Stimulation

Abstract

Brain connectivity profiles seeding from deep brain stimulation (DBS) electrodes have emerged as informative tools to estimate outcome variability across DBS patients. Given the limitations of acquiring and processing patient-specific diffusion-weighted imaging data, most studies have employed normative atlases of the human connectome. To date, it remains unclear whether patient-specific connectivity information would strengthen the accuracy of such analyses. Here, we compared similarities and differences between patient-specific, disease-matched and normative structural connectivity data and retrospective estimation of clinical improvement that they may generate. Data from 33 patients suffering from Parkinson Disease who underwent surgery at three different centers were retrospectively collected. Stimulation-dependent connectivity profiles seeding from active contacts were estimated using three modalities, namely either patient-specific diffusion-MRI data, disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were constructed and used to retrospectively estimate the clinical improvement in out of sample data. All three modalities resulted in highly similar optimal connectivity profiles that could largely reproduce findings from prior research based on a novel multi-center cohort. Connectivity estimates seeding from electrodes when using either patient-specific or normative connectomes correlated significantly to primary motor cortex (R = 0.57, p = 0.001, R=0.73, p=0.001), supplementary motor area (R = 0.40, p = 0.005, R = 0.43, p = 0.003), pre-supplementary motor area (R = 0.33, p = 0.022, R = 0.33, p = 0.031), but not to more frontal regions such as the dorsomedial prefrontal cortex (R = 0.21, p = 0.17, R = 0.18, p = 0.17). However, in a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample estimation of clinical improvements were made and ranged within a similar magnitude when applying either of the three modalities (R = 0.43 at p = 0.001 for patient-specific connectivity; R = 0.25, p = 0.048 for the age- and disease-matched group connectome; R = 0.31 at p = 0.028 for healthy-/young connectome). Conclusions: The use of patient-specific connectivity and normative connectomes lead to identical main conclusions about which brain areas are associated with clinical improvement. Still, although results were not significantly different, they hint at the fact that patient-specific connectivity may bear the potential of estimating slightly more variance when compared to group connectomes. Our findings further support the role of DBS electrode connectivity profiles as a promising method to guide surgical targeting and DBS programming.

Tuber Locations Associated with Infantile Spasms Map to a Common Brain Network

“…However, a large high‐quality functional connectivity dataset from ~2–3‐year‐old children is not currently available, and a direct test of lesion network mapping using an age‐matched connectome is not yet feasible. Nevertheless, we have thus far seen minimal impact from methodological differences in how one processes connectome data, for example, global signal regression versus other artifact removal strategies, 16,54 or using patient‐specific, age‐matched, or disease‐matched normative connectomes, 16,55–58 which is reflected here by the consistent localization of infantile spasm–related connections using data from the ABCD 9‐year‐old group connectome (n = 1,000; see Fig 4E vs Fig 4F). It is possible that our results could be improved by using a connectome better matched to the age of the TSC patients, and this is an experiment we intend to perform once such data become available and extensively processed given the significant confounds present in young child fMRI data.…”

Opportunities of connectomic neuromodulation

“…Recently, groups have begun to directly compare results using patient-specific vs. normative connectomes in DBS ( Wang et al, 2020 ) or TMS ( Cash et al, 2019 ). Both studies found no significant difference between the two connectomes in their ability to predict clinical outcomes, but noted a slight trend towards better prediction with individualized data.…”

Long-Term Outcome and Neuroimaging of Deep Brain Stimulation in Holmes Tremor: A Case Series

“…In addition, there are inaccuracies due to the normalization process since individual anatomical variations of the tract cannot be taken into account. There is some published evidence showing that connectivity profiles for DBS drawn from normative connectomes versus patient‐based connectivity profiles were comparable in respect to brain areas that are associated with clinical improvement (22). However, the spatial normalization of brains with structural deformities (such as often the brains from HT patients) into brain atlases, remains challenging.…”