diff --git a/mne/viz/backends/_pyvista.py b/mne/viz/backends/_pyvista.py
index a5bef386502..50038046e69 100644
--- a/mne/viz/backends/_pyvista.py
+++ b/mne/viz/backends/_pyvista.py
@@ -46,10 +46,7 @@
 from vtkmodules.vtkCommonDataModel import VTK_VERTEX, vtkPiecewiseFunction
 from vtkmodules.vtkCommonTransforms import vtkTransform
 from vtkmodules.vtkFiltersCore import vtkCellDataToPointData, vtkGlyph3D
-from vtkmodules.vtkFiltersGeneral import (
-    vtkMarchingContourFilter,
-    vtkTransformPolyDataFilter,
-)
+from vtkmodules.vtkFiltersGeneral import vtkMarchingContourFilter
 from vtkmodules.vtkFiltersHybrid import vtkPolyDataSilhouette
 from vtkmodules.vtkFiltersSources import (
     vtkArrowSource,
@@ -72,6 +69,13 @@
 )
 from vtkmodules.vtkRenderingVolumeOpenGL2 import vtkSmartVolumeMapper
 
+try:
+    from vtkmodules.vtkFiltersGeneral import vtkTransformFilter
+except ImportError:  # TODO VERSION VTK 9.7+
+    from vtkmodules.vtkFiltersGeneral import (
+        vtkTransformPolyDataFilter as vtkTransformFilter,
+    )
+
 _FIGURES = dict()
 
 
@@ -694,7 +698,7 @@ def quiver3d(
             if tr is not None:
                 # fix orientation
                 glyph.Update()
-                trp = vtkTransformPolyDataFilter()
+                trp = vtkTransformFilter()
                 trp.SetInputData(glyph.GetOutput())
                 trp.SetTransform(tr)
                 glyph = trp
@@ -1263,7 +1267,7 @@ def _arrow_glyph(grid, factor):
     # fix position
     tr = vtkTransform()
     tr.Translate(0.5, 0.0, 0.0)
-    trp = vtkTransformPolyDataFilter()
+    trp = vtkTransformFilter()
     trp.SetInputConnection(glyph.GetOutputPort())
     trp.SetTransform(tr)
     trp.Update()
diff --git a/tutorials/inverse/50_beamformer_lcmv.py b/tutorials/inverse/50_beamformer_lcmv.py
index 7f84476dc3c..59d51d653b0 100644
--- a/tutorials/inverse/50_beamformer_lcmv.py
+++ b/tutorials/inverse/50_beamformer_lcmv.py
@@ -271,12 +271,13 @@
     clim=dict(kind="value", lims=lims),
     hemi="both",
     size=(600, 600),
-    views=["sagittal"],
+    views=["lateral"],
     # Could do this for a 3-panel figure:
     # view_layout='horizontal', views=['coronal', 'sagittal', 'axial'],
     brain_kwargs=dict(silhouette=True),
     **kwargs,
 )
+brain.show_view("lateral", hemi="rh")
 
 # %%
 # Visualize the activity of the maximum voxel with all three components