Functional Imaging to Guide Network-Based TMS Treatments: Toward a Tailored Medicine Approach in Alzheimer's Disease

Abstract

A growing number of studies is using fMRI-based connectivity to guide transcranial magnetic stimulation (TMS) target identification in both normal and clinical populations. TMS has gained increasing attention as a potential therapeutic strategy also in Alzheimer's disease (AD), but an endorsed target localization strategy in this population is still lacking. In this proof of concept study, we prove the feasibility of a tailored TMS targeting approach for AD, which stems from a network-based perspective. Based on functional imaging, the procedure allows to extract individual optimal targets meanwhile accounting for functional variability. Single-subject resting-state fMRI was used to extract individual target coordinates of two networks primarily affected in AD, the default mode and the fronto-parietal network. The localization of these targets was compared to that of traditional group-level approaches and tested against varying degrees of TMS focality. The distance between individual fMRI-derived coordinates and traditionally defined targets was significant for a supposed TMS focality of 12 mm and in some cases up to 20 mm. Comparison with anatomical labels confirmed a lack of 1:1 correspondence between anatomical and functional targets. The proposed network-based fMRI-guided TMS approach, while accounting for inter-individual functional variability, allows to target core AD networks, and might thus represent a step toward tailored TMS interventions for AD.

Keywords: Alzheimer’s disease; connectivity; functional brain networks; repetitive transcranial magnetic stimulation; resting-state fMRI; tailored treatment.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2021 Bagattini, Brignani, Bonnì, Quattrini, Gasparotti and Pievani.

Figures

FIGURE 1

Overview of the procedure for the identification and selection of individual DMN and FPN targets based on rs-fMRI; (A) Collected rs-fMRI data were pre-processed removing the first time-points, correcting motion, and susceptibility-induced distortions; (B) DMN and FPN were extracted from individual rs-fMRI scans using independent component analysis (ICA); (C) Networks of interest (in MNI space) were identified using a template matching procedure; (B,C) were repeated multiple times; (D) The most reliable components were identified and back-transformed to subjects’ native T1 space; (E) Each network was decomposed into clusters and the largest cluster in the left IPL and left DLPFC was identified, for the DMN and FPN, respectively; (F) The peaks (local maxima) within these clusters were extracted and the final individual TMS targets were selected according to the following criteria: (i) location specific to the network of interest, i.e., coordinates falling within the spatial maps of both DMN and FPN (yellow areas) were excluded (blue = DMN, red = FPN); (ii) being on a cortical gyrus and not on a sulcus (i.e., overlap with GM); (iii) representing the shortest perpendicular path between scalp and cortex; (G) TMS coil was positioned through a neuronavigation system to target the selected DMN and FPN coordinates.

FIGURE 2

(A) Location of the individual targets (overlaid onto the standard MNI template) for default mode network (DMN) stimulation (top panel) and frontoparietal network (FPN) stimulation (bottom panel) in thirteen AD patients. Images are shown in radiological convention (left denotes right). The individual targets (green cross) were extracted from each subject’s 3T rs-fMRI data using ICA. The DMN targets correspond to the left IPL cluster, the FPN targets to the left DLPFC cluster. The individual DMN and FPN maps are shown in orange-yellow. The targets were defined in subjects’ native T1 space and back-transformed to the standard MNI space for computation and visualization purposes; (B) 3D render showing the individual targets (red-yellow) overlaid onto the standard MNI template. For the DMN, green target corresponds to P3 (Herwig et al., 2003), and light-blue to IPL (Cotelli et al., 2012). For the FPN, yellow target corresponds to DLPFC BA9 (Fox et al., 2013), light-blue to DLPFC-5 cm rule (Fox et al., 2013), blue to DLPFC BA46 (Fox et al., 2013), red to F3 (Herwig et al., 2003), green to DLPFC BA8/9 (Cotelli et al., 2010). DMN, default mode network; FPN, fronto-parietal network; BA8/9, Broadmann areas 8 and 9; BA9, Broadmann area 9; BA46, Broadmann area 46; IPL, inferior parietal lobule; DLPFC, dorsolateral prefrontal cortex.

FIGURE 3

(A) Location of the individual targets (overlaid onto the standard MNI template) for default mode network (DMN) stimulation (top panel) and frontoparietal network (FPN) stimulation (bottom panel) in eight healthy elderly controls. Images are shown in radiological convention (left denotes right). (B) 3D render showing the individual targets (red-yellow) overlaid onto the standard MNI template. For the DMN, green target corresponds to P3 (Herwig et al., 2003), and light-blue to IPL (Cotelli et al., 2012). For the FPN, yellow target corresponds to DLPFC BA9 (Fox et al., 2013), light-blue to DLPFC-5 cm rule (Fox et al., 2013), blue to DLPFC BA46 (Fox et al., 2013), red to F3 (Herwig et al., 2003), green to DLPFC BA8/9 (Cotelli et al., 2010). DMN, default mode network; FPN, fronto-parietal network; BA8/9, Broadmann areas 8 and 9; BA9, Broadmann area 9; BA46, Broadmann area 46; IPL, inferior parietal lobule; DLPFC, dorsolateral prefrontal cortex.