diff --git a/monai/apps/reconstruction/transforms/dictionary.py b/monai/apps/reconstruction/transforms/dictionary.py
index c166740768..0185974040 100644
--- a/monai/apps/reconstruction/transforms/dictionary.py
+++ b/monai/apps/reconstruction/transforms/dictionary.py
@@ -37,16 +37,19 @@ class ExtractDataKeyFromMetaKeyd(MapTransform):
         keys: keys to be transferred from meta to data
         meta_key: the meta key where all the meta-data is stored
         allow_missing_keys: don't raise exception if key is missing
+        image_only: if True, only extract metadata from MetaTensor images to avoid duplication
 
     Example:
         When the fastMRI dataset is loaded, "kspace" is stored in the data dictionary,
         but the ground-truth image with the key "reconstruction_rss" is stored in the meta data.
         In this case, ExtractDataKeyFromMetaKeyd moves "reconstruction_rss" to data.
+        For MetaTensor objects, setting image_only=True prevents extracting redundant metadata.
     """
 
-    def __init__(self, keys: KeysCollection, meta_key: str, allow_missing_keys: bool = False) -> None:
+    def __init__(self, keys: KeysCollection, meta_key: str, allow_missing_keys: bool = False, image_only: bool = False) -> None:
         MapTransform.__init__(self, keys, allow_missing_keys)
         self.meta_key = meta_key
+        self.image_only = image_only
 
     def __call__(self, data: Mapping[Hashable, NdarrayOrTensor]) -> dict[Hashable, Tensor]:
         """
@@ -60,7 +63,12 @@ def __call__(self, data: Mapping[Hashable, NdarrayOrTensor]) -> dict[Hashable, T
         d = dict(data)
         for key in self.keys:
             if key in d[self.meta_key]:
-                d[key] = d[self.meta_key][key]  # type: ignore
+                extracted_value = d[self.meta_key][key]
+                # When image_only is True, skip if the extracted value is a MetaTensor
+                # to preserve metadata associations
+                if self.image_only and isinstance(extracted_value, MetaTensor):
+                    continue
+                d[key] = extracted_value  # type: ignore
             elif not self.allow_missing_keys:
                 raise KeyError(
                     f"Key `{key}` of transform `{self.__class__.__name__}` was missing in the meta data"
diff --git a/monai/handlers/tensorboard_handlers.py b/monai/handlers/tensorboard_handlers.py
index 20e2d74c8c..0a69ccfaba 100644
--- a/monai/handlers/tensorboard_handlers.py
+++ b/monai/handlers/tensorboard_handlers.py
@@ -50,6 +50,11 @@ class TensorBoardHandler:
 
     def __init__(self, summary_writer: SummaryWriter | SummaryWriterX | None = None, log_dir: str = "./runs"):
         if summary_writer is None:
+            if SummaryWriter is None:
+                raise RuntimeError(
+                    "TensorBoardHandler requires tensorboard to be installed. "
+                    "Please install it with: pip install tensorboard"
+                )
             self._writer = SummaryWriter(log_dir=log_dir)
             self.internal_writer = True
         else:
diff --git a/monai/transforms/croppad/functional.py b/monai/transforms/croppad/functional.py
index 653db43bc5..572d01ea1d 100644
--- a/monai/transforms/croppad/functional.py
+++ b/monai/transforms/croppad/functional.py
@@ -96,12 +96,7 @@ def pad_nd(
         return _np_pad(img, pad_width=to_pad, mode=mode, **kwargs)
     try:
         _pad = _np_pad
-        if mode in {"constant", "reflect", "edge", "replicate", "wrap", "circular"} and img.dtype not in {
-            torch.int16,
-            torch.int64,
-            torch.bool,
-            torch.uint8,
-        }:
+        if mode in {"constant", "reflect", "edge", "replicate", "wrap", "circular"}:
             _pad = _pt_pad
         return _pad(img, pad_width=to_pad, mode=mode, **kwargs)
     except (ValueError, TypeError, RuntimeError) as err: