diff --git a/monai/transforms/spatial/dictionary.py b/monai/transforms/spatial/dictionary.py
index e8118ffda0..01fadcfb69 100644
--- a/monai/transforms/spatial/dictionary.py
+++ b/monai/transforms/spatial/dictionary.py
@@ -517,7 +517,8 @@ def __call__(self, data: Mapping[Hashable, torch.Tensor], lazy: bool | None = No
                 output_spatial_shape=output_shape_k if should_match else None,
                 lazy=lazy_,
             )
-            output_shape_k = d[key].peek_pending_shape() if isinstance(d[key], MetaTensor) else d[key].shape[1:]
+            if output_shape_k is None:
+                output_shape_k = d[key].peek_pending_shape() if isinstance(d[key], MetaTensor) else d[key].shape[1:]
         return d
 
     def inverse(self, data: Mapping[Hashable, NdarrayOrTensor]) -> dict[Hashable, NdarrayOrTensor]:
diff --git a/tests/test_spacingd.py b/tests/test_spacingd.py
index 78f6ad454b..36986b2706 100644
--- a/tests/test_spacingd.py
+++ b/tests/test_spacingd.py
@@ -83,6 +83,20 @@
             *device,
         )
     )
+    TESTS.append(
+        (
+            "interp sep",
+            {
+                "image": MetaTensor(torch.ones((2, 1, 10)), affine=torch.eye(4)),
+                "seg1": MetaTensor(torch.ones((2, 1, 10)), affine=torch.diag(torch.tensor([2, 2, 2, 1]))),
+                "seg2": MetaTensor(torch.ones((2, 1, 10)), affine=torch.eye(4)),
+            },
+            dict(keys=("image", "seg1", "seg2"), mode=("bilinear", "nearest", "nearest"), pixdim=(1, 1, 1)),
+            (2, 1, 10),
+            torch.as_tensor(np.diag((1, 1, 1, 1))),
+            *device,
+        )
+    )
 
 TESTS_TORCH = []
 for track_meta in (False, True):