Presurgical Assessment of the Sensorimotor Cortex Using Resting-State fMRI

Discussion

Presurgical localization of the eloquent cortex is clearly one of the keys to reducing postsurgery motor deficits and reaching an optimal patient outcome. Among the functional imaging techniques, rs-fMRI has been commonly used in neuroscience and has now attracted interest for clinical applications.^20,21 Compared with tb-fMRI, rs-fMRI has some practical advantages: shorter scanning times and a simple setup. It is less sensitive to subject-related deficiencies such as paresis, paralysis, or lack of attention, and it is easier to apply to children. Here, we demonstrated that rs-fMRI is capable of consistently mapping the motor cortex with a spatial precision that is necessary in clinical settings (ie, discrimination of foot, hand, and face representations). The probability of identifying different body representations by using rs-fMRI is equivalent to that of tb-fMRI. Nevertheless, unequal results were obtained in different parts of the motor cortex: The largest body part representation (hand) was the easiest to detect and the most consistent among readers (Table 2). Our findings are in line with those of Liu et al,¹³ who studied 6 patients with tumors or epileptic foci near the motor cortex before surgery. The visual evaluation of their results led to good agreement between rs-fMRI and tb-fMRI, which included hand and tongue movements. We also measured the overlap between rs- and tb-fMRI through concurrent ratios. The average value was approximately 30%, which is in agreement with the findings of Tie et al,²² who assessed concurrent ratios in healthy individuals.

Of several methods that can be used to analyze tb-fMRI data,²³ we used SPM, and dissimilar results may be obtained with other software. Particularly, different strategies can be applied to deal with the multiple-testing problem when analyzing tb-fMRI data.^24,25 No consensus has been reached on which one to use in the context of individual patient analysis. We investigated 2 different approaches to correct for multiple comparisons in our work: a test based on the cluster size and another based on voxel intensity. The cluster size correction is known to have increased sensitivity when the signal is spatially extended^19,25; this result is likely when attempting to detect the activity of the sensorimotor cortex. The sensitivity of both tests was similar and approximately 95% in our data (Table 2). However, when comparing tb- and rs-fMRI spatial maps, we observed different overlap depending on the multiple-comparison technique; concurrent ratios were larger with the correction at the voxel level.

Of note, both the rs-ICs and the tb-activation maps did not exclusively show the motor cortex. tb-fMRI revealed a somatotopic segment of the motor cortex and can display nonspecific activations. rs-fMRI motor components showed the whole motor cortex and were typically bilateral (Fig 1). To limit the impact of this problem, we segmented the spatial maps resulting from rs- and tb-fMRI analyses. However, the outcome usually showed regions larger than the primary motor cortex (Fig 2). This effect frequently occurred when using the cluster correction because it is more likely to expose large clusters of activity and may explain the lower concurrent ratios obtained when using this test.

Most previous studies testing rs-fMRI clinical feasibility used cross-correlation techniques.^{11,13⇓–15} This approach requires the definition of a seed region based on anatomy or additional functional exploration, to reveal correlations between the average signal time course of voxels within the ROI and the time courses of the other brain voxels. The approach we used here (ICA) does not require any prior knowledge of the temporal or spatial patterns of brain responses. ICA is a popular mathematic approach that maximizes statistical independence among its components to identify distinct resting-state networks. A practical drawback that can be attributed to ICA is that the user must choose among dozens of functional components, which most probably reflect neurofunctional systems over noise. This selection is often made by visual inspection. Other strategies have been imagined to assist the IC selection. Kokkonen et al¹² used a template-matching method, for which each IC was spatially correlated to a motor tb-fMRI template. The authors reported successful results in 8 patients with brain tumors. Nevertheless, to avoid adding any prior spatial knowledge in our analyses, we chose another strategy to analyze our rs-fMRI data. Visual review of the calculated ICs for every patient was thus made by 3 radiologists blinded to each other and to the results of tb-fMRI. Additionally, a novel data-driven method has been recently tested at the individual level in patients with epilepsy and tumors.²⁶ It showed promising results and may resolve some of the limitations of cross-correlation analysis (structural seed definition) and ICA (postanalysis IC selection).

A tb-fMRI examination including movement of the hand, face, and foot gives satisfactory coverage of the motor cortex for many clinical purposes. The number of studied body parts has to be adapted to the lesion location. Nonetheless, when considering a large lesion, one must examine the entire motor cortex of the injured hemisphere and one may also be interested in mapping the normal motor representation in the contralateral hemisphere. This process leads to long scanning times and may not be adapted to every patient, especially when the functional exploration is combined with morphologic and/or spectroscopic acquisitions.

Case 9 relates to a 12-year-old child with a glioma, for whom the whole MR imaging examination may have been too long and too demanding to be entirely and satisfactorily completed. Indeed, the tb-fMRI explorations of both feet did not give any significant results. Alternatively, both complete motor cortices were then identified by using rs-fMRI in <7 minutes. Because a long scanning time is the most frequent difficulty for the schedule of tb-fMRI examinations, rs-fMRI is a convincing surrogate and can be more easily integrated with other MR imaging investigations. For another case (15), the patient had difficulty performing the task because of a Dupuytren contracture. This led to nonsignificant and uninterpretable results by using tb-fMRI. This case illustrates the limits of tb-fMRI in a clinical environment where it is difficult to design a specific task for each patient. In contrast, rs-fMRI results were informative.

Additionally, we showed that rs-fMRI can be successfully performed by using 2 different MR imaging systems (1.5T and 3T). Nevertheless, we report a better ability to detect the motor cortex at 3T and a trend toward a better similarity between rs-and tb-fMRI spatial maps at 3T (Table 3). Indeed, the spatial specificity of tb-fMRI increases with the strength of the magnetic field.²⁷ Moreover, because the amplitude of spontaneous blood oxygen level–dependent fluctuations is also likely to increase with field strength, it is then not surprising to find a better intersection between rs- and tb-fMRI results at 3T.

Generalizability in real-life clinical settings is usually a critical step when developing new techniques. Here, we successfully tested rs-fMRI in a prospective study, involving a typical patient list of our department by using 2 different clinical MR imaging systems. Sensitivity was comparable with that of tb-fMRI with fewer practical acquisition issues. The IC selection process still needs to be standardized and automated in some way to allow rs-fMRI to be largely used for clinical planning before surgery. Moreover, preliminary studies characterizing the accuracy of rs-fMRI showed promising results.^15,26 These findings constitute the groundwork for the establishment of rs-fMRI in surgical planning. However, improved patient outcome has yet to be demonstrated, to firmly establish the clinical utility of rs-fMRI.