Optimization of the Navigated TMS Mapping Algorithm for Accurate Estimation of Cortical Muscle Representation Characteristics

Transcranial magnetic stimulation mapping of the motor cortex: comparison of five estimation algorithms

Background

There are currently five different kinds of transcranial magnetic stimulation (TMS) motor mapping algorithms available, from ordinary point-based algorithms to advanced field-based algorithms. However, there have been only a limited number of comparison studies conducted, and they have not yet examined all of the currently available algorithms. This deficiency impedes the judicious selection of algorithms for application in both clinical and basic neuroscience, and hinders the potential promotion of a potential superior algorithm. Considering the influence of algorithm complexity, further investigation is needed to examine the differences between fMRI peaks and TMS cortical hotspots that were identified previously.

Methods

Twelve healthy participants underwent TMS motor mapping and a finger-tapping task during fMRI. The motor cortex TMS mapping results were estimated by five algorithms, and fMRI activation results were obtained. For each algorithm, the prediction error was defined as the distance between the measured scalp hotspot and optimized coil position, which was determined by the maximum electric field strength in the estimated motor cortex. Additionally, the study identified the minimum number of stimuli required for stable mapping. Finally, the location difference between the TMS mapping cortical hotspot and the fMRI activation peak was analyzed.

Results

The projection yielded the lowest prediction error (5.27 ± 4.24 mm) among the point-based algorithms and the association algorithm yielded the lowest (6.66 ± 3.48 mm) among field-based estimation algorithms. The projection algorithm required fewer stimuli, possibly resulting from its suitability for the grid-based mapping data collection method. The TMS cortical hotspots from all algorithms consistently deviated from the fMRI activation peak (20.52 ± 8.46 mm for five algorithms).

Conclusion

The association algorithm might be a superior choice for clinical applications and basic neuroscience research, due to its lower prediction error and higher estimation sensitivity in the deep cortical structure, especially for the sulcus. It also has potential applicability in various other TMS domains, including language area mapping and more. Otherwise, our results provide further evidence that TMS motor mapping intrinsically differs from fMRI motor mapping.

Mapping of Motor Function with Neuronavigated Transcranial Magnetic Stimulation: A Review on Clinical Application in Brain Tumors and Methods for Ensuring Feasible Accuracy

Navigated transcranial magnetic stimulation (nTMS) has developed into a reliable non-invasive clinical and scientific tool over the past decade. Specifically, it has undergone several validating clinical trials that demonstrated high agreement with intraoperative direct electrical stimulation (DES), which paved the way for increasing application for the purpose of motor mapping in patients harboring motor-eloquent intracranial neoplasms. Based on this clinical use case of the technique, in this article we review the evidence for the feasibility of motor mapping and derived models (risk stratification and prediction, nTMS-based fiber tracking, improvement of clinical outcome, and assessment of functional plasticity), and provide collected sets of evidence for the applicability of quantitative mapping with nTMS. In addition, we provide evidence-based demonstrations on factors that ensure methodological feasibility and accuracy of the motor mapping procedure. We demonstrate that selection of the stimulation intensity (SI) for nTMS and spatial density of stimuli are crucial factors for applying motor mapping accurately, while also demonstrating the effect on the motor maps. We conclude that while the application of nTMS motor mapping has been impressively spread over the past decade, there are still variations in the applied protocols and parameters, which could be optimized for the purpose of reliable quantitative mapping.

Mapping of multiple muscles with transcranial magnetic stimulation: absolute and relative test-retest reliability

The spatial accuracy of transcranial magnetic stimulation (TMS) may be as small as a few millimeters. Despite such great potential, navigated TMS (nTMS) mapping is still underused for the assessment of motor plasticity, particularly in clinical settings. Here, we investigate the within-limb somatotopy gradient as well as absolute and relative reliability of three hand muscle cortical representations (MCRs) using a comprehensive grid-based sulcus-informed nTMS motor mapping. We enrolled 22 young healthy male volunteers. Two nTMS mapping sessions were separated by 5-10 days. Motor evoked potentials were obtained from abductor pollicis brevis (APB), abductor digiti minimi, and extensor digitorum communis. In addition to individual MRI-based analysis, we studied normalized MNI MCRs. For the reliability assessment, we calculated intraclass correlation and the smallest detectable change. Our results revealed a somatotopy gradient reflected by APB MCR having the most lateral location. Reliability analysis showed that the commonly used metrics of MCRs, such as areas, volumes, centers of gravity (COGs), and hotspots had a high relative and low absolute reliability for all three muscles. For within-limb TMS somatotopy, the most common metrics such as the shifts between MCR COGs and hotspots had poor relative reliability. However, overlaps between different muscle MCRs were highly reliable. We, thus, provide novel evidence that inter-muscle MCR interaction can be reliably traced using MCR overlaps while shifts between the COGs and hotspots of different MCRs are not suitable for this purpose. Our results have implications for the interpretation of nTMS motor mapping results in healthy subjects and patients with neurological conditions.

Spatial extent of cortical motor hotspot in navigated transcranial magnetic stimulation

BACKGROUND

Motor mapping with navigated transcranial magnetic stimulation (nTMS) requires defining a "hotspot", a stimulation site consistently producing the highest-amplitude motor-evoked potentials (MEPs). The exact location of the hotspot is difficult to determine, and the spatial extent of high-amplitude MEPs usually remains undefined due to MEP variability and the spread of the TMS-induced electric field (E-field). Therefore, here we aim to define the hotspot as a sub-region of a motor map.

NEW METHOD

We analyzed MEP amplitude distributions in motor mappings of 30 healthy subjects in two orthogonal directions on the motor cortex. Based on the widths of these distributions, the hotspot extent was estimated as an elliptic area. In addition, E-field distributions induced by motor map edge stimulations were simulated for ten subjects, and the E-field attenuation was analyzed to obtain another estimate for hotspot extent.

RESULTS

The median MEP-based hotspot area was 13 mm² (95% confidence interval (CI) = [10, 18] mm²). The mean E-field-based hotspot area was 26 mm² (95% CI = [13, 38] mm²).

COMPARISON WITH EXISTING METHODS

In contrast to the conventional hotspot, the new definition considers its spatial extent, indicating the most easily excited area where subsequent nTMS stimuli should be targeted for maximal response. The E-field-based hotspot provides an estimate for the extent of cortical structures where the E-field is close to its maximum.

CONCLUSIONS

The nTMS hotspot should be considered as an area rather than a single qualitatively defined spot due to MEP variability and E-field spread.