Quantifying the axonal pathways directly stimulated in therapeutic subcallosal cingulate deep brain stimulation

Abstract

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) is an emerging experimental therapy for treatment-resistant depression. New developments in SCC DBS surgical targeting are focused on identifying specific axonal pathways for stimulation that are estimated from patient-specific computational models. This connectomic-based biophysical modeling strategy has proven successful in improving the clinical response to SCC DBS therapy, but the DBS models used to date have been relatively simplistic, limiting the precision of the pathway activation estimates. Therefore, we used the most detailed patient-specific foundation for DBS modeling currently available (i.e., field-cable modeling) to evaluate SCC DBS in our most recent cohort of six subjects, all of which were responders to the therapy. We quantified activation of four major pathways in the SCC region: forceps minor (FM), cingulum bundle (CB), uncinate fasciculus (UF), and subcortical connections between the frontal pole and the thalamus or ventral striatum (FP). We then used the percentage of activated axons in each pathway as regressors in a linear model to predict the time it took patients to reach a stable response, or TSR. Our analysis suggests that stimulation of the left and right CBs, as well as FM are the most likely therapeutic targets for SCC DBS. In addition, the right CB alone predicted 84% of the variation in the TSR, and the correlation was positive, suggesting that activation of the right CB beyond a critical percentage may actually protract the recovery process.

Keywords: computational model; connectomic; pathway activation.

Conflict of interest statement

CCM is a shareholder in Surgical Information Sciences, as well as a paid consultant to Boston Scientific Neuromodulation and Kernel. HSM is a paid consultant with licensed intellectual property to Abbott Neuromodulation. All other authors reported no biomedical financial interests or potential conflicts of interests.

© 2018 Wiley Periodicals, Inc.

Figures

Figure 1

Image‐based volume conductor model of Patient 2. (a1) Sagittal and (a2) coronal views of patient's head segmented into 12 different regions. Knowledge of the locations and electrical properties of the different head regions was used to construct a volume conductor model of the patient's head. (b1) Artifacts produced by the Medtronic 3387 leads in the postoperative computed tomography image were identified using regions of minimal intensity within the artifacts and (b2) orthogonal distance regression was used to fit a straight trajectory to the intra‐artifact regions (red arrows). The 3387 leads were modeled as surfaces within the volume conductor model. D = dorsal; A = anterior; M = medial; Lat = lateral

Figure 2

Candidate therapeutic pathways in Patient 2. Probabilistic tractography was used to define (a) one interhemispheric pathway, forceps minor (red streamlines) and three intrahemispheric pathways per hemisphere: (b) cingulum bundle (yellow streamlines), (c) uncinate fasciculus (blue streamlines), and (d) subcortical projections from the frontal pole to the thalamus and ventral striatum (green streamlines). Active contacts are in pink. D = dorsal; A = anterior; M = medial; Lat = lateral [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 3

Quantifying responses of cable models to SCC DBS in Patient 2. (a1) Temporal variation in the potentials at the electrode–tissue interface. (a2) Spatial variation in the potentials over forceps minor and cingulum bundle. Only a subset of axons is displayed for visualization purposes. (b1) Active axons were those that responded one‐to‐one to the applied stimulus pulses during interleaved stimulation. (b2) The axons directly activated at the clinical settings. SCC = subcallosal cingulate; DBS = deep brain stimulation [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 4

Predicted and measured dynamic resistances. (a) Dynamic resistances measured by the implantable pulse generator 70 μs after the onset of the stimulus pulse (i.e., R70) in Patient 6. Contact 0 (C0) is closest to the tip. Although R70 were monitored weekly for the first year and every 2 months thereafter, we only analyzed R70 between 50 and 200 days after surgery (dashed lines), when the measurements were relatively stable. (b) The predicted R70 versus the average R70 that was measured 50–200 days post‐surgery in all six patients; the bars for the IPG data denote ±1 standard deviation. Because the fourth contact (C3) on the right lead was broken in Patient 3, no measured values for this contact are shown [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 5

Axons directly activated by SCC DBS. Streamlines indicate the axon models directly activated by the extracellular stimulus at each patient's clinical setting: 130 Hz, 4 V, 90 μs, monopolar cathodic configuration (pink). All axons had a fiber diameter of 2 μm, and right and left denotes the responses when either the right or left lead is active. Percentages denote the percentage of each pathway that is activated. FM = forceps minor; CB = cingulum bundle; UF = uncinate fasciculus; FP = subcortical connections from frontal pole to thalamus and ventral striatum; L = left; R = right [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 6

Predicting the time to a stable response (TSR). (a) TSR as a function of the percentage of axons activation in the right cingulum bundle (CBR). R2 = coefficient of determination. (b) Regression coefficients for CBR across all 720 permutations of TSR in the six patients. The red line denotes the value for the regression coefficient when TSR is not permuted [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 7

Estimating responses of 5.7 μm‐diameter axons with FC PAM versus VTA PAM. (a) Axons activated in the right hemisphere of Patient 2 at their clinical setting: 4 V, 90 μs, 130 Hz, electrode 1 (pink). For the VTA PAM, axons were considered active when they intersected the VTA (black ellipsoid). D = dorsal; M = medial; Lat = lateral; L = left; R = right. (b) Percentage of FM activated by the right lead in Patient 2 at various amplitudes. (c) Errors in voltage stimulation thresholds (Vth) between the FC and VTA PAMs of each patient. Errors are aggregated across contacts two and three (C1 and C2, respectively) and all pathways. (d) Vth (mean ± 1 standard deviation) versus the electrode‐to‐axon distance (de2a) for each pathway. de2a is the minimum distance from the axon to the surface of the active electrode. Values were averaged across both leads/hemispheres and all patients. FM = forceps minor; CB = cingulum bundle; UF = uncinate fasciculus; FP = connections from the frontal pole to the thalamus and ventral striatum; FC = field‐cable; VTA = volume of tissue‐activated; PAM = pathway activation model [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 8

Role of axon diameter in models of SCC DBS. Previous FC‐ and VTA‐based analyses assumed a fiber diameter (D) of 5.7 μm (black and red), whereas the patient‐specific FC PAMs in this work used 2.0 μm (blue). Thresholds (±1 standard error of the mean) and distances are averaged across all patients, hemispheres, and pathways. Vth = activation threshold for stimulation; de2a = minimum electrode‐to‐axon distance; SCC = subcallosal cingulate; DBS = deep brain stimulation; FC = field‐cable; VTA = volume of tissue‐activated; PAM = pathway activation model [Color figure can be viewed at http://wileyonlinelibrary.com]