diff --git a/FastSurferCNN/segstats.py b/FastSurferCNN/segstats.py
index 3f2769fe..3a106375 100644
--- a/FastSurferCNN/segstats.py
+++ b/FastSurferCNN/segstats.py
@@ -876,7 +876,8 @@ def main(args: argparse.Namespace) -> Literal[0] | str:
         pv_data = pv_preproc_future.result()
 
     names = ["nbr", "nbr_means", "seg_means", "mix_coeff", "nbr_mix_coeff"]
-    save_maps = any(getattr(args, n, "") for n in names)
+    save_maps_paths = (getattr(args, n, "") for n in names)
+    save_maps = any(bool(path) and path != Path() for path in save_maps_paths)
     out = pv_calc(seg_data, pv_data, norm_data, labels, return_maps=save_maps, **kwargs)
 
     _io_futures = []
diff --git a/FastSurferCNN/utils/brainvolstats.py b/FastSurferCNN/utils/brainvolstats.py
index e06a06cf..bc9ca9af 100644
--- a/FastSurferCNN/utils/brainvolstats.py
+++ b/FastSurferCNN/utils/brainvolstats.py
@@ -714,7 +714,6 @@ def __init__(
         self._classes = classes
         super().__init__(name, description, unit)
         self._pv_value = None
-        self._vox_vol = 0.
 
     @property
     def vox_vol(self) -> float:
@@ -736,12 +735,8 @@ def __call__(self) -> float:
                 f"The partial volume of {self._name} has not been updated in the "
                 f"PVMeasure object yet!"
             )
-        if self.unit == "unitless":
-            vox_vol, col = 1, "NVoxels"
-        else:
-            vox_vol, col = self._vox_vol, "Volume_mm3"
-        out = self._pv_value[col].item() * vox_vol
-        return out
+        col = "NVoxels" if self.unit == "unitless" else "Volume_mm3"
+        return self._pv_value[col].item()
 
     def _parsable_args(self) -> list[str]:
         return ["classes"]
@@ -2191,8 +2186,7 @@ def mask_77_lat(arr):
                 brain_seg_classes.extend(range(2002, 2032))
                 brain_seg_classes.remove(2004)
                 brain_seg_classes.extend((2034, 2035))
-            brainseg_class = self.voxel_class
-            return brainseg_class(
+            return self.voxel_class(
                 brain_seg_classes,
                 "BrainSegVol",
                 "Brain Segmentation Volume",