Resection of cerebellar tumours causes widespread and functionally relevant white matter impairments

Abstract

Several diffusion tensor imaging studies reveal that white matter (WM) lesions are common in children suffering from benign cerebellar tumours who are treated with surgery only. The clinical implications of WM alterations that occur as a direct consequence of cerebellar disease have not been thoroughly studied. Here, we analysed structural and diffusion imaging data from cerebellar patients with chronic surgical lesions after resection for benign cerebellar tumours. We aimed to elucidate the impact of focal lesions of the cerebellum on WM integrity across the entire brain, and to investigate whether WM deficits were associated with behavioural impairment in three different motor tasks. Lesion symptom mapping analysis suggested that lesions in critical cerebellar regions were related to deficits in savings during an eyeblink conditioning task, as well as to deficits in motor action timing. Diffusion imaging analysis of cerebellar WM indicated that better behavioural performance was associated with higher fractional anisotropy (FA) in the superior cerebellar peduncle, cerebellum's main outflow path. Moreover, voxel-wise analysis revealed a global pattern of WM deficits in patients within many cerebral WM tracts critical for motor and non-motor function. Finally, we observed a positive correlation between FA and savings within cerebello-thalamo-cortical pathways in patients but not in controls, showing that saving effects partly depend on extracerebellar areas, and may be recruited for compensation. These results confirm that the cerebellum has extended connections with many cerebral areas involved in motor/cognitive functions, and the observed WM changes likely contribute to long-term clinical deficits of posterior fossa tumour survivors.

Keywords: cerebellum; diffusion tensor imaging; eyeblink conditioning; lesion-symptom mapping; motor skill learning.

FIGURE 1

Schematic descriptions and experimental paradigms of the different motor tasks. Eyeblink conditioning: (a) Schematic illustration, (b) experimental paradigm (reproduced from Ernst et al., 2016). Metronome task: (c) Snapshot of the task, and (d) timing schedule. Cart‐pole balancing task: (e) Snapshot of the task, (f) haptic input device for the metronome and cart‐pole tasks. (g) Experimental schedule for the metronome and cart‐pole tasks over the five consecutive days

FIGURE 2

Cerebellar lesion extent displayed on a normalised cerebellum. (a) Outline of lesion for the first nine (top row) and last nine (middle row) cerebellar participants. (b) Lesion overlap. Colourbar indicates the number of patients with lesions on those voxels. (c) SUIT template (Diedrichsen, 2006) overlaid on top of one representative participant's B0 image in diffusion space, showing accurate registration of the lobules (coloured outlines) and cerebellar peduncles (bold red outlines). Note: Lesions are displayed in the original hemisphere in which they occurred. For the analysis of voxel‐based lesion symptom mapping, the left‐hemisphere lesions were flipped horizontally to the right hemisphere

FIGURE 3

Results of the multivariate voxel‐based lesion‐symptom mapping (VBLSM). For the eyeblink conditioning task, only the Savings parameter showed significant correlations. CP‐AT, Cart‐Pole Action timing; M‐SE, Metronome Synchronisation error; ICARS, International Cooperative Ataxia Rating Scale (Trouillas et al., 1997)

FIGURE 4

(a–c) Correlations between FA and behavioural performance within the superior peduncle for the eyeblink conditioning task. (a) Identification of an apparent “outlier” (red dot). (b) Removal of the “outlier” did not substantially change the resulting slopes and associated standard errors. (c) Same plot as (a) but colour‐coded to distinguish between cerebellar and control participants' performance. (d) Correlation between FA and behavioural performance for the metronome (M‐SE) and cart‐pole balancing tasks (CP‐AT)

FIGURE 5

Tract‐based spatial statistics (TBSS) results for the group comparison. Top two rows show the results for the contrast cerebellar < control participants for the FA (light) and MD (right) metrics. The bottom two rows show the results for the opposite contrast (cerebellar > control participants). Red‐yellow colour shows which voxels surviving correction for multiple comparisons (FWE‐corrected p < .05), which shows the white matter skeleton (threshold 0.3–0.7)

FIGURE 6

Tract‐based spatial statistics (TBSS) results comparing group slopes with fractional anisotropy (FA) values. (a) Results for the contrast testing the cerebellar > control participants' slopes for the Savings measure of the eyeblink conditioning task. Red‐yellow colour shows voxels surviving correction for multiple comparisons (FWE‐corrected p < .05), white shows the white matter skeleton (threshold 0.3–0.7). (b) Voxel values in (a) were extracted and FA values plotted against behavioural scores for each of the extinction learning measures. Thick lines show the overall direction of the effect (i.e., across all significant voxels). Thin lines show the regression slopes for each individual ROI (with >30 significant voxels; see also Table S3). (c) Overlap between the contrast map shown in (a) (red) and the cerebellar < control participants contrast from Figure 4 (green). Yellow shows voxels that were common in both contrasts. (d) Overlay showing the 48 white‐matter tracts from ICBM‐DTI‐81 atlas (Mori et al., 2008), which were used to create the figure in (b)

FIGURE 7

Tract‐based spatial statistics (TBSS) results for the cerebellar participant group only, testing which voxels show a correlation with the M‐SE. Blue colour indicate voxels that were short of significance (p < .09) after correcting for multiple comparisons, white shows the white matter skeleton (threshold 0.3–0.7)