diff --git a/monai/transforms/io/array.py b/monai/transforms/io/array.py
index 049779f606..aadd96763d 100644
--- a/monai/transforms/io/array.py
+++ b/monai/transforms/io/array.py
@@ -299,7 +299,7 @@ def __call__(self, filename: Sequence[PathLike] | PathLike, reader: ImageReader
             img_array, meta_data, self.simple_keys, pattern=self.pattern, sep=self.sep
         )
         if self.ensure_channel_first:
-            img = EnsureChannelFirst()(img)
+            img = EnsureChannelFirst()(img, meta_dict=meta_data)
         if self.image_only:
             return img
         return img, img.meta if isinstance(img, MetaTensor) else meta_data
diff --git a/tests/transforms/test_load_image.py b/tests/transforms/test_load_image.py
index 031e38272e..4a470a624c 100644
--- a/tests/transforms/test_load_image.py
+++ b/tests/transforms/test_load_image.py
@@ -25,7 +25,7 @@
 
 from monai.apps import download_and_extract
 from monai.data import NibabelReader, PydicomReader
-from monai.data.meta_obj import set_track_meta
+from monai.data.meta_obj import get_track_meta, set_track_meta
 from monai.data.meta_tensor import MetaTensor
 from monai.transforms import LoadImage
 from monai.utils import optional_import
@@ -497,6 +497,17 @@ def test_correct(self, input_param, expected_shape, track_meta):
             self.assertNotIsInstance(r, MetaTensor)
             self.assertFalse(hasattr(r, "affine"))
 
+    def test_track_meta_false_ensure_channel_first(self):
+        _previous_meta = get_track_meta()
+        try:
+            set_track_meta(False)
+            r = LoadImage(image_only=True, ensure_channel_first=True)(self.test_data)
+            self.assertTupleEqual(r.shape, (1, 128, 128, 128))
+            self.assertIsInstance(r, torch.Tensor)
+            self.assertNotIsInstance(r, MetaTensor)
+        finally:
+            set_track_meta(_previous_meta)
+
 
 if __name__ == "__main__":
     unittest.main()