diff --git a/monai/metrics/utils.py b/monai/metrics/utils.py
index a5927a0a5b..ea9bdd0727 100644
--- a/monai/metrics/utils.py
+++ b/monai/metrics/utils.py
@@ -359,9 +359,7 @@ def get_edge_surface_distance(
     edges_spacing = None
     if use_subvoxels:
         edges_spacing = spacing if spacing is not None else ([1] * len(y_pred.shape))
-    edges_pred, edges_gt, *areas = get_mask_edges(
-        y_pred, y, crop=True, spacing=edges_spacing, always_return_as_numpy=False
-    )
+    edges_pred, edges_gt, *areas = get_mask_edges(y_pred, y, crop=True, spacing=edges_spacing)
     if not edges_gt.any():
         warnings.warn(
             f"the ground truth of class {class_index if class_index != -1 else 'Unknown'} is all 0,"
diff --git a/tests/metrics/test_metrics_internal_deprecation.py b/tests/metrics/test_metrics_internal_deprecation.py
new file mode 100644
index 0000000000..b3fee35694
--- /dev/null
+++ b/tests/metrics/test_metrics_internal_deprecation.py
@@ -0,0 +1,89 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import pathlib
+import unittest
+import warnings
+
+import torch
+
+import monai
+from monai.metrics import HausdorffDistanceMetric, SurfaceDistanceMetric
+from monai.utils import optional_import
+
+binary_erosion, has_scipy = optional_import("scipy.ndimage", name="binary_erosion")
+
+_MONAI_ROOT = str(pathlib.Path(monai.__file__).parent.resolve())
+
+
+def _internal_deprecation_warnings(fn):
+    """Collect deprecation-style warnings raised from inside the MONAI package itself.
+
+    Warnings originating in third-party packages are ignored, so this is not affected by
+    unrelated deprecations in torch or numpy.
+
+    Args:
+        fn: zero-argument callable to invoke while warnings are being recorded.
+
+    Returns:
+        list of `warnings.WarningMessage`: the recorded `DeprecationWarning` and
+        `FutureWarning` entries whose originating file lies inside the MONAI package.
+        Empty when the call raised no MONAI-internal deprecation warnings.
+    """
+    with warnings.catch_warnings(record=True) as caught:
+        warnings.simplefilter("always")
+        fn()
+    return [
+        w
+        for w in caught
+        if issubclass(w.category, (DeprecationWarning, FutureWarning))
+        and _MONAI_ROOT in str(pathlib.Path(w.filename).resolve())
+    ]
+
+
+@unittest.skipUnless(has_scipy, "Requires scipy.")
+class TestMetricsNoInternalDeprecationWarnings(unittest.TestCase):
+    """Metrics must not trigger MONAI's own deprecation warnings via internal call sites.
+
+    `SurfaceDistanceMetric` and `HausdorffDistanceMetric` both route through
+    `monai.metrics.utils.get_edge_surface_distance`. If that helper passes a deprecated
+    argument to `get_mask_edges`, every metric computation emits a warning that the caller
+    never triggered and cannot suppress.
+
+    Both metrics compute mask edges via `scipy.ndimage`, so this test is skipped when
+    scipy is unavailable.
+    """
+
+    def test_surface_and_hausdorff_emit_no_internal_deprecation_warnings(self):
+        """Assert neither metric raises a MONAI-internal deprecation warning.
+
+        Computes each metric on a fixed pair of 2D binary masks and fails if any
+        `DeprecationWarning` or `FutureWarning` originating inside MONAI is recorded.
+        """
+        pred = torch.zeros(1, 1, 32, 32)
+        pred[..., :16, :] = 1
+        gt = torch.zeros(1, 1, 32, 32)
+        gt[..., :20, :] = 1
+
+        for metric in (SurfaceDistanceMetric(), HausdorffDistanceMetric()):
+            with self.subTest(metric=type(metric).__name__):
+                found = _internal_deprecation_warnings(lambda m=metric: m(pred, gt))
+                self.assertEqual(
+                    [str(w.message) for w in found],
+                    [],
+                    f"{type(metric).__name__} raised MONAI-internal deprecation warning(s)",
+                )
+
+
+if __name__ == "__main__":
+    unittest.main()