diff --git a/pandas/core/ops/array_ops.py b/pandas/core/ops/array_ops.py
index 9153eb25032e7..6f6972c34f0a9 100644
--- a/pandas/core/ops/array_ops.py
+++ b/pandas/core/ops/array_ops.py
@@ -195,6 +195,8 @@ def arithmetic_op(left: ArrayLike, right: Any, op):
 
     # NB: We assume that extract_array has already been called
     #  on `left` and `right`.
+    # We need to special-case datetime64/timedelta64 dtypes (e.g. because numpy
+    # casts integer dtypes to timedelta64 when operating with timedelta64 - GH#22390)
     lvalues = ensure_wrapped_if_datetimelike(left)
     rvalues = ensure_wrapped_if_datetimelike(right)
     rvalues = _maybe_upcast_for_op(rvalues, lvalues.shape)
@@ -439,11 +441,6 @@ def _maybe_upcast_for_op(obj, shape: Shape):
     Be careful to call this *after* determining the `name` attribute to be
     attached to the result of the arithmetic operation.
     """
-    from pandas.core.arrays import (
-        DatetimeArray,
-        TimedeltaArray,
-    )
-
     if type(obj) is timedelta:
         # GH#22390  cast up to Timedelta to rely on Timedelta
         # implementation; otherwise operation against numeric-dtype
@@ -453,6 +450,8 @@ def _maybe_upcast_for_op(obj, shape: Shape):
         # GH#28080 numpy casts integer-dtype to datetime64 when doing
         #  array[int] + datetime64, which we do not allow
         if isna(obj):
+            from pandas.core.arrays import DatetimeArray
+
             # Avoid possible ambiguities with pd.NaT
             obj = obj.astype("datetime64[ns]")
             right = np.broadcast_to(obj, shape)
@@ -462,6 +461,8 @@ def _maybe_upcast_for_op(obj, shape: Shape):
 
     elif isinstance(obj, np.timedelta64):
         if isna(obj):
+            from pandas.core.arrays import TimedeltaArray
+
             # wrapping timedelta64("NaT") in Timedelta returns NaT,
             #  which would incorrectly be treated as a datetime-NaT, so
             #  we broadcast and wrap in a TimedeltaArray
@@ -474,9 +475,4 @@ def _maybe_upcast_for_op(obj, shape: Shape):
         #  np.timedelta64(3, 'D') / 2 == np.timedelta64(1, 'D')
         return Timedelta(obj)
 
-    elif isinstance(obj, np.ndarray) and obj.dtype.kind == "m":
-        # GH#22390 Unfortunately we need to special-case right-hand
-        # timedelta64 dtypes because numpy casts integer dtypes to
-        # timedelta64 when operating with timedelta64
-        return TimedeltaArray._from_sequence(obj)
     return obj