Silvina G Horovitz1, Nora Vanegas-Arroyave1,2, Ling Huang2, Peter M Lauro2, Paul A Taylor3,4,5, Mark Hallett1, Kareem A Zaghloul6, and Codrin Lungu2
1Human Motor Control Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, United States, 2Office of the Clinical Director, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, United States, 3Scientific and Statistical Computing Core, National Institutes of Health, Bethesda, MD, United States, 4Department of Human Biology, Faculty of Health Sciences, University of Cape Town, MRC/UCT Medical Imaging Research Unit, Cape Town, South Africa, 5African Institute for Mathematical Sciences, Muizenberg, South Africa, 6Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, United States
Synopsis
Deep brain stimulation (DBS) of the subthalamic nucleus
(STN) is an effective surgical treatment for Parkinson’s Disease (PD). However,
its mechanism is unclear. We have developed a pipeline for processing diffusion
tensor imaging (DTI) data in DBS patients, and applied it to analyze 22 PD
patients implanted with bilateral
STN-DBS. With this approach, we have identified the motor nuclei of the
thalamus and the superior frontal cortex as the most common targets and
predictors of clinical benefits.Purpose
Deep brain stimulation (DBS) of the subthalamic nucleus
(STN) is an effective surgical treatment for Parkinson’s Disease (PD). The
therapeutic mechanism of STN-DBS remains unclear. Diffusion tensor imaging
(DTI) is an MRI based method that allows the evaluation of white matter
pathways in vivo. We hypothesize that
the investigation of relevant networks using DTI will add to the understanding
of the mechanism of action for DBS. Here
we present a method for DBS-DTI analysis and study the structural connectivity
patterns of clinically effective STN stimulation in PD patients.
Methods
We
studied the stimulator-brain connectivity patterns in twenty-two patients with
idiopathic PD (12 females, age 58.8±8.6 years, disease duration 13.4±6.3 years). All underwent
standard STN-DBS implantation (DBS lead Model 3389, Medtronic, Minneapolis, Minnesota, USA) bilaterally. One month after surgery, patients
underwent initial monopolar screening of the four electrodes of each lead. T1-,
T2- and diffusion-weighted (b=1000 s/mm2, 32 directions) MR images
were collected on at 3T (Philips Achieva XT) preoperatively, and T1-weighted MR (1.5T) (Philips Achieva XT), and CT images (Siemens SOMATOM Definition Flash) were collected
postoperatively. We developed a publicly available pipeline for DBS-DTI data
analysis within the AFNI environment (DBSproc1). After pre-processing images in TORTOISE2,
our pipeline performs the following actions (Figure 1):
1) multi-modal image co-registration
within native patient space,
2) electrode reconstruction from
T2-space-linked postoperative CT images,
3) estimation of volume of tissue
activated (VTA) for each electrode based on stimulation voltage and impedance,
4) computation of connectivity between the
VTA and brain ROIs from FreeSurfer3 segmentation assessed with
probabilistic tractography using FATCAT4 (sample tractography result in Figure 2).
For clinically
effective electrodes, we identified the most prevalent ROIs for subcortical and
cortical regions performing a binary analysis of connections (>1% of total
streamlines from the VTA). We then assessed whether connectivity
strength to these regions could be an indicator of clinical effectiveness.
Specifically, for each ROI and within each lead, we used a simple
connection-based classifier to identify whether the electrode with highest
connectivity to the ROI indicates clinical effectiveness.
Results
At three and six months after surgery, all patients
demonstrated significant benefits (pre- vs post-operative, p<0.0001) with
STN-DBS, as illustrated by reductions in UPDRS-IV (complications of therapy
assessment) and LEDD (requirement of dopaminergic medications) scores. An
initial screening session identified 123 clinically effective electrodes in 40
hemispheres. Four hemispheres were undetermined because the contralateral body-side
was asymptomatic. Proper registration and electrode localization were
successful in all patients (quality assessment in Figure 3).
Binary analysis of the probabilistic tractography of the VTA
showed that 96% of clinically effective electrodes had connections to the thalamus
and 98% to the brainstem. Within the cortical regions, the superior frontal
gyrus (SFG) was the most prevalent connection (56%)(Figure 4).
Connection-based classifiers were tested for 38 leads that
contained at least one electrode with clinical benefits. Classification
accuracy (highest connectivity was beneficial electrode) was 87% for the
thalamus, 71% for the brainstem and 94% for the SFG.
In a post-hoc analysis, we assessed connectivity between the
VTA and thalamic nuclei (derived from a Talairach-Tournoux atlas) for all of
the clinically effective electrodes using tractography. 95% of clinically
effective electrodes reached at least one motor thalamic nucleus (93%
ventrolateral and 85% ventroanterior nucleus).
Discussion
Thalamus and SFG were identified
as the most “desirable” targets in STN-DBS. Our findings are in line with
previous studies suggesting that the modulation of white matter structures in
the vicinity of the dorsal STN may be implicated in its mechanism of action. In
agreement with electrophysiological and PET studies,5,6 projections
to specific motor subnuclei of the thalamus might be particularly implicated in
the motor benefits observed with STN-DBS. Further brainstem segmentation/parcellation might allow the
differentiation of individual subnuclei associated with relevant motor circuits
in the basal ganglia. Further research is warranted.
Acknowledgements
NINDS Intramural ProgramReferences
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